We then test whether K12 discrimination in transfer can lead to biased transfer towards other K12 cells in a well-mixed population and subsequent selection of the better donor strain.

We compete the K12 and B strains by mixing them equally in a well-mixed population, with a common proportion of cells from each strain initially bearing R1-19 plas- mid.

In the absence of antibiotic selection, the better donor K12 decreases in frequency (Fig 2C, dark blue), showing a lower basal fitness than B in those culture conditions.

When antibi- otic selection is applied at the end of the competition by plating the population on kanamycin (Kn)-containing medium, only Kn-resistant, plasmid-bearing cells grow.

When all cells ini- tially bear plasmids, selection does not favour the K12 strain (Fig 2C orange, 19% decrease in K12 frequency, two sided t test for difference from 0, p = 0.003).

However, when only a fraction (2.5%) of both K12 and B cells initially bear R1-19 plasmid, providing opportunity for plasmid transfer, K12 is selected (19% increase in K12 frequency, two sided t test for difference from 0, p = 0.009).

Finally, to confirm that this specific selection of donors is due to R1-19 transfer to K12 cells, we analyse the outcome of competition when the arcA gene is deleted from K12 and transfer is impaired.

In the absence of antibiotic selection (Fig 2C, light blue), the arcA deletion does not affect K12 fitness when plasmids are absent or rare and increases K12 fitness when all cells bear plasmids (11% decrease for K12ΔarcA versus 25% decrease for K12, two-sided t test, p = 0.043), possibly because of the reduced plasmid cost for K12ΔarcA. With antibiotic selec- tion, the specific selection of K12 when a fraction of cells bear plasmids disappears for K12ΔarcA (Fig 2C middle, yellow bars, two-sided t test, p = 2.10 −5 ), demonstrating that K12 selection was due to plasmid transfer.

Discrimination effectively biases antibiotic resistance transfer strongly enough so that the better donor K12 strain is selected for in the presence of antibiotics.

Thus, when transferred plasmids are needed for growth, discrimination in transfer towards kind, at naturally appearing levels, can be sufficient to select for the better donor.


A second possible reason for transfer bias is bacterial growth in structured populations, where donors interact preferentially with their kind.


Next, we examine whether, in the absence of dis- crimination, structured populations can provide a sufficient bias in transfer to select for good donors.


To analyse the effect of biased transfer in structured populations, we use a synthetic system with fluorescently tagged plasmids in which we can identify plasmid transfer between two strains.


We adapted the system from the one we designed for an earlier study on interac- tion between conjugation and cooperation [6].


A helper plasmid F HR , that is nonmobile and thus behaves like a chromosomal allele, governs the host cell donor ability for a mobile plasmid C, which confers chloramphenicol (Cm) resistance.


We compete (Fig 3A) two strains differing in their donor ability: the good donor D + strain bears F HR that transfers C plasmids, and the nondonor D − strain does not (S2A Fig).


After a transfer phase (t 0 to t 1 ), populations are grown with or without Cm during the selection phase (t 1 to t 2 ).


We compare a single, well-mixed pop- ulation (m), where D + and D − are mixed in equal proportions, to a structured metapopulation (s), consisting of two subpopulations that grow separately during the transfer phase, s 1 and s 2 , founded respectively with a 10% and 90% proportion of D + (leading to equal proportions of D + Bacterial Altruism Promotes Horizontal Gene Transfer PLOS Biology | DOI:10.1371/journal.pbio.1002478 June 7, 2016 8 / 28 and D − at the metapopulation level).


In this setup, the changes in the good donor frequency can be followed both within and among populations to evaluate the effect of population struc- ture on donor selection.


D + strain frequency does not change significantly in m or s populations during the transfer phase (Fig 3B left).

D + frequency then increases at t 2 only for the structured s population grown in the presence of Cm (Fig 3B right, 26% increase from t 0 , Mann-Whitney Wilcoxon test, p = 0.004).

It decreases for m population with Cm (19% decrease, two-sided t test for dif- ference from 0, p = 3.10 −9 ) and stays constant in the absence of Cm.

The dynamics generally follows our predictions: D + selection requires both population structure and plasmid selection.

However, the expected cost of D + during the transfer phase is not present at the population level.

We next investigate in more detail both this cost and the selection of the good donor strain.


By looking at the dynamics of individual subpopulations during the transfer phase, we observed that D + increases in frequency when prevalent (S3A Fig).

We confirmed with an inde- pendent experiment that D + fitness in competition with D − linearly increases with D + fre- quency (S3B Fig).

This positive frequency-dependence for donor fitness could be due to lethal zygosis, a phenomenon known to damage recipients at high donor cell frequencies [41], which could be aggravated by the absence of entry exclusion in our strains [42].

In natural systems, entry exclusion may protect new transconjugants but would also make initial plasmid-bearing donors immune to lethal zygosis, probably leading to a similar frequency-dependence of fitness when most donor cells initially bear plasmids.

In our system, frequency-dependence leads to no observable cost for D + at the metapopulation level.

At low frequencies, donor ability still has a cost, which is also observed as a decrease in the strain's growth rate when growing in iso- lation (D + versus D − , S2C Fig).

Interestingly, donor cells grow significantly more slowly when they bear C plasmids, which is not the case for nondonor cells (D + C versus D − C , S2C Fig), sug- gesting that donor ability cost is enhanced by the presence of transferable plasmids in the cell.


During the selection phase, good donors are selected only in the structured s population and only in the presence of Cm, meaning that donor selection requires both population structure during the transfer phase and subsequent antibiotic selection.

We see that, as predicted by our model, biased transfer due to population structure promotes indirect selection of the donor strain.

To better understand the factors affecting D + selection, we proceed to analyse the dynamics of C plasmids (Fig 3C).

During the transfer phase, plasmid frequency changes depend on the proportion of cells able to transfer.


In the s 1 population where D + cells are few, plasmid frequency declines slightly.

It increases mostly in the s 2 population enriched in D + strain.

Increases are due to transfer, as the increase in plasmids present in D − strain is due to plasmids that originate from D + (as identified by fluorescence markers, see Materials and Methods and S4 Fig).

We then follow the proportion of C plasmids that are present in D + cells, as plasmid localization controls survival in the presence of antibiotics.


During the transfer phase, the proportion of C plasmids present in D + cells compared to D − cells decreases in the well-mixed m population (13% decrease, Mann-Whitney Wilcoxon test, p = 0.004) but increases in the structured s population (28% increase, Mann-Whitney Wilcoxon test, p = 0.004) (Fig 3D).

In the well-mixed population, the decrease is probably due to the strong fitness cost D + cells incur specifically when they bear C plasmids (S2 Fig).

The same cost also explains the subsequent decrease in D + strain frequency under Cm selection in both popula- tions.


The enrichment of C plasmids in D + cells depends on the population structure of the s population: total plasmid transfer is more prevalent in the s 2 subpopulation, effectively biasing transfer towards D + at the metapopulation level.

These results experimentally confirm our models prediction: in the absence of discrimination mechanisms, donor ability for antibiotic resistance plasmids can be selected when population structure ensures preferential transfer to cells sharing donation alleles.


So far, we have shown that both discrimination and population structuring can select for donor ability.

However, we have always assumed and ensured that discrimination and popula- tion structure are present in the system.

Here, we study how both phenomena can themselves emerge.


When analysing effects of population structure, we imposed starting proportions of both the strains and the plasmids in order to dissect the dynamics of transfer.

We continue by study- ing the outcome of competitions arising in more natural population structures using simula- tions.

In the absence of a mechanism for discrimination of recipients, our model suggests that population structure may influence the selection of donor ability in two opposing ways (Eq 3).

Efficient transfer is favoured by the coexistence of plasmid-bearing and plasmid-free cells within patches, while biased transfer towards kind is favoured by high relatedness at the dona- tion locus.

The selection of transfer thus requires preferential interactions between cells sharing donor ability alleles but also sufficient cell mixing that would favour the encounter between Bacterial Altruism Promotes Horizontal Gene Transfer PLOS Biology | DOI:10.1371/journal.pbio.1002478 June 7, 2016 10 / 28 plasmid-bearing and plasmid-free cells.


To study the effects of a natural population structure and the possibility that both conditions are met simultaneously, we simulate strong population dilution, which leads to stochastic founder cell numbers and genotype frequencies [6,33].

We follow the frequency of the donor D + strain in a simulated metapopulation initiated from a strongly diluted mix of equal proportions of D + and D − .

With growth parameters based on our experimental results, we vary both the dilution factor applied to founding populations and the proportion of plasmid-bearing cells (Fig 4).

The results exhibit a clear pattern: the donor strain is selected under the combination of strong initial dilution and low initial plasmid frequency.


D + selection in the presence of antibiotics is controlled primarily by the enrichment of plas- mids in D + at t 1 (S5A Fig), which occurs when there is biased transfer towards D + during the transfer phase.

As predicted by Eq 3, biased transfer requires high relatedness at the donation locus but also effective transfer, which will be affected by dilution and initial plasmid preva- lence.

First, diluting down to low founding cell numbers provides sufficient variation in D + fre- quencies among populations to ensure high relatedness (S5B Fig).

Second, the contribution of transfer to plasmid abundance declines with increasing dilution and increasing plasmid initial abundance (S5C Fig).


Transfer promotes plasmid invasion primarily when plasmid-bearing cells are initially scarce, because in those conditions, the majority of plasmid-bearing cells actu- ally arise from transfer.

Increasing dilution leads to the frequent absence of one of the cell types from each population, which in turn decreases the number of possible encounters between plasmid-bearing and plasmid-free cells.

Selection for donor ability is strongest at high dilution because of high relatedness; however, dilution simultaneously limits transfer, which decreases the strength of selection compared to the optimal population structure studied in Fig 3.

Overall, our simulations suggest that the conditions for selection of donor ability can be met in natural environments through limited dispersal alone, despite the trade-off between relatedness and transfer efficiency that arises from population structure.


We now focus on the association between discrimination mechanisms and plasmid transfer, which was apparent in natural isolates data (Fig 2A) and ask how this association itself could emerge.

The effect on donor ability (Fig 2B and Fig 2C) suggests that a genotype bearing both discrimination and high donor ability alleles could be favoured by selection.

We consider as an example the case of a strain inactivated at a chromosomal restriction-modification locus: such a mutant appearing in a wild type population will transfer plasmids preferentially to clone- mates bearing the same allele, as unmodified plasmids transferred from this mutant will be degraded in a wild-type recipient cell [38,39].

The mutant allele with no modification is denoted by M − , and the wild type allele by M + , D + , and D − stand for high and low donor ability, as before.

We use simulations to follow the dynamics of modification and donation alleles, in populations of cells with no initial association between M − and D + .


In a well-mixed population (analogous to the one studied in Fig 2C), the M − allele is selected for, but the D + is not (Fig 5A, left).

Discrimination in transfer by M − cells leads to a reduced total transfer to M + cells, and direct selection of M − with comparatively higher recipient ability.

D + cells are outcompeted, as they do not receive more plasmids than D − cells in the absence of association to M − alleles.

On the contrary, in a population where D + cell frequency differs sufficiently among subpopula- tions, both M − and D + alleles are selected for (Fig 5A, right): similarly to the dynamics pre- sented in Fig 3, population structure biases transfer towards D + cells, allowing for D + selection in the presence of antibiotics.


Linkage between M − and D + alleles is also controlled by popula- tion structure (Fig 5B): with antibiotic selection, positive linkage appears when D + cell fre- quency varies among subpopulations.

This does not occur in the absence of antibiotics, suggesting that linkage is due to the specific selection of plasmid-bearing cells.

With increasing D + population structure, most plasmids end up in D + M − cells (Fig 5C) due to the combined effect of higher recipient ability and biased transfer by D + cells.

We conclude that the Bacterial Altruism Promotes Horizontal Gene Transfer PLOS Biology | DOI:10.1371/journal.pbio.1002478 June 7, 2016 11 / 28 association between discrimination and transfer alleles can emerge simply through selection of plasmid-bearing cells, when population structure ensures that cells with high donor ability are favoured.


Selective pressures acting on donor ability depend on the fitness effects of genes carried by the transmitted plasmids.

Here, we focus on mutualistic antibiotic resistance plasmids, but para- sitic and mutualistic plasmids can coexist in host populations, and hosts may not be able to evolve differential control of transfer based only on the accessory genes plasmids carry.

Next, we consider the presence of parasitic plasmids N, which are similar to mutualistic plasmids C but do not confer benefits during the selection phase (see S2B Fig and Materials and Methods).

In simulations, increase in the initial proportion of parasitic plasmids lead to a decrease in final frequency of the good donor strain (S6 Fig).

We can conclude that the strength of selection for donor ability decreases when donors encounter a mix of mutualistic and parasitic plasmids, as they cannot distinguish between the two plasmid types.

However, the benefits conferred by mutualistic plasmids could indirectly favour their association to the host.


To study the association between plasmids and hosts, we measure experimentally and with simulations the linkage disequilibrium between plasmids and the good donor allele in a meta- population similar to the previous one (Fig 3) but now with a mix of C and N plasmids in equal proportions instead of only C plasmids, and with no initial association between plasmids and a specific strain (each plasmid is equally present in D + and D - strains).

After the transfer phase, both C and N plasmids become significantly linked to the good donor D + strain in the struc- tured population, but not in the well-mixed population (Fig 6A, left).

Moreover, after Cm selec- tion, linkage to D + slightly increases for C plasmids but decreases to zero for N plasmids in the structured population and remains at zero in the well-mixed population (Fig 6A, right, plain lines).

Finally, this pattern relies on the specific selection of C-bearing cells: when selecting with Kn (an antibiotic to which both plasmids confer resistance) instead of Cm, linkage decreases to zero for both plasmids (dashed lines).

Our experiments show that linkage between plasmids and good donor cells arises only when two specific conditions are met: (1) the popula- tion is structured, and (2) plasmids are beneficial.


To better understand the factors controlling the association, we independently vary D + donor ability and C plasmid beneficial effect on the host strain fitness in our simulations.

The linkage that appears at t 1 between both plasmids and D + strain increases with D + donor ability, independently of subsequent plasmid benefits (S7A Fig).

This linkage arises because transfer is biased towards D + cells at the metapopulation level (as seen in Fig 3).

In our experiments, the observed linkage is stronger for N plasmids because they are preferentially transferred.


At t 2 , however, C plasmid benefits modify the linkage patterns.

With increasing C benefits, C linkage to D + increases (Fig 6B), and N linkage to D + decreases (S7B Fig), when donor ability is suffi- ciently high.

The specific association between C plasmids and the donor strain thus arises from the benefits provided by C plasmids to the host: antibiotics promote the selection of cells bear- ing C plasmids, which are mainly good donor cells because of previous transfer.

Overall, this mechanism selects for cells simultaneously bearing both D + and C alleles.

Linkage between the good donor strain and beneficial plasmids arises without directly enforcing any association between the two, due to the combination of two effects: population structure biasing transfer towards good donor cells and the plasmids benefiting the host.


Our work investigates the evolution of host genes controlling the transfer of mutualistic MGEs such as those conferring antibiotic resistance.

We focus on genes modulating plasmid dona- tion, a property that, unlike plasmid reception, does not directly benefit the host.

Earlier inter- pretations have described MGEs as a communal pool of genes conferring benefits at the population level [2,18].

We demonstrate here that donor ability, when it is costly to the host, is not selected directly.

However, we do not need to invoke population-level benefits to explain why the host may promote MGE transfer.

Instead, we show that host donor ability alleles can be selected indirectly when transfer increases their inclusive fitness (Fig 1).

We then investigate further this qualitative result by measuring selection direction and strength in simulations as well as experiments using both natural and synthetic microbes, in situations close to ones that could be observed in nature.


In the absence of discrimination, population structure is a simple mechanism ensuring that cells encounter preferentially neighbours of the same kind.

Here, we demonstrate that in a syn- thetic biological system devoid of any mechanism for discrimination in transfer, population structure enables the selection of donor ability, biasing plasmid transfer prior to the selection of plasmid-bearing cells (Fig 3).

Donor ability is not selected within well-mixed populations where donors do not interact preferentially with their kind, and good donors decline in fre- quency due to donor ability costs.

However, donor ability is selected at a metapopulation scale, where population structure provides sufficient relatedness at the locus controlling donor abil- ity.

With simulations, we then show that populations with sufficient relatedness can arise sim- ply through strong population dilution, despite the reduction in transfer due to fewer interactions between plasmid-bearing and plasmid-free cells (Fig 4).


Further, we experimentally demonstrate that differences in transfer rates between isolates, leading to effective discrimination in transfer, can also be sufficiently high to favour a strain with high donor ability (Fig 2).

In natural isolates, we observe discrimination for the transfer of an antibiotic resistance plasmid.


These results motivate future studies that would quantify the generality of discrimination by examining other plasmids and strains, as well as determine the underlying mechanisms.

Discrimination can result from specific recognition during cell-cell contact [30] or even direct spread through the cytoplasm of clonemates in the case of bacterial chains [43].


Alternatively, discrimination can arise during the establishment of plasmids in recipient cells.

In particular, plasmid transfer rate is greatly diminished when restriction-modi- fication systems present in recipients differ from those in donor cells [9,38,39].

At a larger phy- logenetic scale, a plasmid host range can be limited by its mechanisms of replication or transfer [44].


Even when plasmids are successfully transferred, they need not confer any fitness benefit, because genes beneficial in the initial donor may be suboptimal in a novel, unfamiliar host [45], favouring a donor strain over distant competitors in which the transferred accessory genes are not fully beneficial.


Finally, discrimination may rely on quorum-sensing mechanisms regulating transfer [46], which can provide an indication of the local abundance of related cells.


Biased transfer to kind can thus happen in host cells that differ from others at a single locus modulating donor ability in structured populations; the benefits of transfer then promote the emergence of discriminating genotypes through linkage with a second locus determining the specificity of transfer.

Population structure plays a central role, allowing both the spread of donor alleles in the absence of discrimination mechanisms and the emergence of discrimination.


As the selective pressures we describe here are indirect, they may be too weak to have a signifi- cant effect on the evolution of transfer rates.

To examine this, we calculate selection coefficients acting on the donor allele in our experiments and simulations.

The strength of selection observed for the discriminating strain K12 in competition with B is high (s = 0.35, S8 Fig).

As the degree of discrimination displayed by K12 is close to the average one measured across Bacterial Altruism Promotes Horizontal Gene Transfer PLOS Biology | DOI:10.1371/journal.pbio.1002478 June 7, 2016 15 / 28 natural isolates (Fig 2A), this result suggests that selection of donor strains that transfer prefer- entially to their kind may occur widely in nature, even in unstructured populations.


In the structured populations we studied, the strength of selection depends on the details of popula- tion structure: when relatedness at the donor ability locus is high but plasmids are present in each strain in equal abundance, donors are again efficiently selected for in our experiments (s = 0.10, S9 Fig).

When both parameters are controlled purely by initial dilution, they behave in opposing ways and selection is lower (S10 Fig, s = 0.0025 in the optimal case).

In natural populations, selection arising through population structure might thus be weaker than the one due to discrimination in transfer and vary depending on the details of host and plasmid popu- lation dynamics.


Still, bacteria are characterized by large population sizes, leading to estimates of effective population sizes around 10 7 [47,48], which implies that mutations with selection coefficients larger than 10 −7 can be selected for [49].

Thus, even in the presence of a trade-off between relatedness and transfer efficiency, selection acting on hosts can result in biologically significant changes in transfer rates.


In the long-term, continued selection for transfer requires that plasmids do not spread to fixa- tion.

As plasmid transfer itself increases plasmid prevalence in host populations, selection for donors will be progressively decreased with plasmid spread.

However, many factors may con- tribute to maintaining plasmids at intermediate frequencies in bacterial populations.


Accessory genes on plasmids are often beneficial in transient or local conditions [50,51] and could be repeatedly lost when they are not selected for.

Plasmid-free segregants occur regularly and will rapidly invade populations when plasmids are costly.

Other factors like the presence of bacteri- ophages can also lead to unstable dynamics, increasing plasmid loss [52].

Moreover, transfer is strongly regulated as a function of environmental conditions [8] and could be induced specifi- cally in the conditions where plasmid-bearing cells are favoured.


A striking case of such a sce- nario are mobile elements providing tetracycline resistance, whose transfer is induced by subinhibitory concentrations of tetracycline [53]: transfer occurs in conditions where mobile elements are likely to increase host fitness in the near future, as indicated by antibiotic gradi- ents.

Regulation of plasmid transfer will also modify the cost of transfer to the host.

In our model, we assumed that plasmid-bearing cells experience a constitutive cost proportional to donor ability, leading to a higher cost to donor genotypes when plasmids are abundant.

Trans- fer can be repressed when plasmid-free cells are likely to be rare [46], leading to the expression of transfer genes only when transfer efficiency is maximised.


Finally, on a wider scale, cell migration between populations that experience different selection pressures for plasmid traits strongly increases the potential for horizontal transfer, as the immigration of plasmid-free cells in populations where plasmid traits are beneficial prevents plasmid fixation and allows sus- tained transfer [54].


Transferring plasmids increases the donor allele inclusive fitness because it enriches cells of the same kind with beneficial alleles.

This phenomenon can be compared to the evolution of teaching in animals: teaching of adaptive information can be selected when teachers and pupils are related [55].

The difference between genetic information transfer in bacteria and cultural transmission is that beneficial genes are by default also transmitted vertically (together with the donor allele), making transfer ineffective if they are already prevalent in the population.

Thus in order to be selected, horizontal transfer needs to improve transmission to kind compared to vertical transmission.

Indeed, horizontal transfer is selected mostly when initially only few cells bear plasmids (Fig 4 and S5C Fig), as in these conditions it allows a more rapid and efficient spread than vertical transfer.

Interestingly, the phenomenon of lethal zygosis suggested by the positive frequency-depen- dence observed in our synthetic system (S3 Fig) [41,42] could act on the selection of donor abil- ity in a complementary way, by selecting for donor genotypes when plasmids are prevalent.

Transfer would then be a spiteful behaviour, in this case, not because of the indirect effects of transferred genes but due to the direct damage to recipient cells.


Bacteria frequently encounter parasitic MGE decreasing fitness.

Eq 3 suggests that the transfer of parasitic elements could be selected if it can be preferentially directed towards cells of another kind.

The spread of parasites has been suggested to be a typical case of spiteful behav- iour, since the donors may be immune to the negative effects of their parasites [56].

Bacterio- phages are a well-known example, where phage lysogeny ensures that most cells of the initial strain are protected from lysis and phages preferentially lyse the cells of a competing strain, at the same time ensuring phage spread [57].

Similar mechanisms are not yet known for plasmids.

However, transfer to unrelated cells is well described in the case of the Ti plasmid of Agrobac- terium tumefasciens, where the T-DNA is transferred to plant cells [58], and specific transfer and gene expression ensure that another species produces resources.

Even with no specific tar- geting, suboptimal effects of transferred genes could render the plasmid harmful, damaging specifically unrelated recipients and effectively leading to spite.


We conclude that the inclusive fitness benefits conferred by transferred plasmids can lead to indirect selection for host donor ability.

Plasmid transfer rates thus can be shaped not only by their direct effects on plasmid fitness [7] but also by their indirect effects on host fitness.

The direction and strength of selection acting on donor ability will depend on the potential for plas- mid transfer, its bias towards kind, the fitness effects of plasmids present in the host popula- tion, and the costs of transfer.

Thus, all these factors might, at least in part, determine both the strikingly large variability of transfer rates observed among bacterial isolates [11,12] and the existence of high donor ability strains.


Our findings have consequences in the context of the fight against the spread of antibiotic resistance, as the indirect selection of donor strains could promote widespread dissemination of antibiotic resistance.

Treatments that decrease the spread of MGEs have already been con- sidered, like male-specific phages that inhibit plasmid transfer but also kill preferentially the cells that actively transfer plasmids [59].

Our work suggests that, the same as for other coopera- tive behaviours [60], bacteria resistant to such treatments may evolve, but relatively slowly [61], which should be taken into account when aiming to diminish horizontal transfer [62].


More generally, our results underline the active role hosts may play in the evolution of transfer rates and the necessity to take bacterial social interactions into account when studying plasmid transfer.

Plasmids themselves often bear public good genes involved in host sociality and interaction with neighbouring cells [5,20], and plasmid transfer promotes host public good production by modifying relatedness in structured populations [6].

The indirect benefits of added public good production may in turn further favour the hosts that are investing in transfer.


Finally, we show that biased transfer in structured populations combined with selection of plasmid-bearing cells promotes association between hosts with high donor ability, discrimina- tion mechanisms (Fig 5), and beneficial plasmids (Fig 6).

Donor ability can be selected in the absence of initial linkage with discrimination alleles or mutualistic plasmids, but selection itself creates linkage at the population level.

This dynamic will alleviate the cost of parasitic plasmids Bacterial Altruism Promotes Horizontal Gene Transfer PLOS Biology | DOI:10.1371/journal.pbio.1002478 June 7, 2016 17 / 28 and lead to a prevalence of donor strains associated with mobile, transiently beneficial plas- mids.

In the long term, the phenomenon could promote mutualistic coevolution between bene- ficial plasmids and strains that transmit them at high rates to their kind, in a way analogous to the evolution of mutualism between species.

The benefits generated by mutualism can create an association between mutualistic partners [63], while the association itself favours further mutualism [64,65].

Plasmids would be a special case of mutualism, with a complex and impor- tant role of horizontal transmission, a mechanism that is generally expected to inhibit mutual- ism [66] but here actually benefits both partners.

Social selection promotes host investment in plasmid transfer, increasing plasmid fitness but simultaneously promoting host association to mutualist plasmids.

This will likely lead to complex social selective pressures acting on plas- mids themselves and shape the mobile gene pool.


To test for discrimination, the better plasmid donor was the Escherichia coli K12 strain MG1655 red , which is MG1655 [35] marked with the td−Cherry gene.

The worse donor was the E. coli B strain REL606 [36].

To measure conjugation rates, two spontaneous mutants resistant to rifampicin (Rif R ) for each strain MG1655 and REL606 were used as recipients.

The plasmid used was the multiresistant R1-19 plasmid (that provides resistance to Cm, sulfonamides, ampicillin, Kn, streptomycin, and spectinomycin) [37].

The K12ΔarcA strain was MG1655 red transduced with the Keio collection arcA deletion mutant [67].


To test for transfer selection in structured populations, we used two synthetic strains, D − and D + , and two associated plasmids, C and N. D − strain is E. coli K12 MG1655.

D + strain is a derivative of MG1655 marked with the td−Cherry gene and bearing the helper plasmid F HR .

F HR is a variant of the F plasmid with low self-transfer and entry exclusion [6], which provides efficient mobilization of plasmids carrying F oriT sequence.

N plasmids bear F oriT and an aph gene providing Kn resistance, while C plasmids additionally carry a cat gene providing Cm resistance.

N and C plasmids express either YFP or GFP under control of the strong promoter P R .

For selection experiments (Fig 3), D − strain initially bears C-GFP plasmid, and D + strain initially bears C-YFP plasmid, in order to identify the origin of C plasmid (see S2A Fig).

For linkage experiments (Fig 6), C-YFP and N-GFP plasmids were used respectively as C and N plasmids (see S2B Fig).


F HR and N-GFP plasmids and their construction are described in detail in [6] (where N-GFP was called the T + P − plasmid).

N-YFP was constructed by amplification of YFP sequence with primers AGCGACTCGAGGATAAATATCTAACACCGTGCGTGTTGAC and AGCACAAG CTTTTCCCGGGTCATTATTTGTATAG, then ligation of N-GFP plasmid and the PCR prod- uct after digestion with XhoI and HindIII.

To construct C plasmids, the cat gene was amplified from pKD3 plasmid [68] with primers TACTAAGACGTCAGGAACTTCATTTAAATGGCG and TACTAGCTCGAGAAGAGGTTCCAACTTTCACC.

The PCR product was ligated into the corresponding (GFP or YFP) N plasmid after digestion with AatII and XhoI.


The D + and MG1655 red strains were constructed by integration of the pRNA1-tdCherry gene construction on pNDL32 plasmid obtained from Nathan Lord (Paulsson laboratory, Har- vard Medical School).

pNDL32 was transformed into MG1655 with selection on 100 μg/mL ampicillin, then streaked twice at 30°C on LB-agar (Luria-Bertani, BD Difco).

Colonies were streaked overnight on LB-agar at 42°C, and plasmid loss was confirmed by checking that clones were ampicillin-sensitive.

F HR was finally added to D + strain by conjugation.

To construct Bacterial Altruism Promotes Horizontal Gene Transfer PLOS Biology | DOI:10.1371/journal.pbio.1002478 June 7, 2016 18 / 28 K12ΔarcA, the Keio collection arcA deletion mutant was used for P1 transduction of MG1655 red, then the kan resistance cassette was removed with pCP20 plasmid [68].


Spontaneous Rif R mutants of MG1655 red and REL606 were obtained by plating overnight cultures on LB-agar with Rif (Sigma-Aldrich) at 100 μg/mL.


Experiments were conducted under well-mixed conditions with 5 mL medium in 50 mL tubes (Sarstedt).

Exponential growth rates (S1 Fig and S2C Fig) were measured in a Tecan Infinite M200 reader on 100 μL cultures with 50 μL mineral oil (Sigma) in 96-well plates, after 100-fold dilution from stationary phase cultures.


For the experiments focusing on discrimination (Fig 2B and Fig 2C), cells were grown at 37°C in M9 minimal medium (BD Difco), with 0.4% glucose and appropriate antibiotics for precultures (Rif, 100 μg/mL for Rif R mutants; Kn, 50 μg/mL for R1-19 plasmid-bearing cells).


To measure conjugation rates (Fig 2B), stationary phase cultures of donor (plasmid-bear- ing) and recipient (Rif R ) strains were washed to remove antibiotics.

They were then diluted 1/ 50 into fresh M9 medium and grown separately at 37°C until the cultures reached an OD (600 nm) of 0.2.

500 μL aliquots of donor and recipient cultures were then mixed and incubated at 37°C for 15 min, limiting secondary transfer.

When ΔarcA mutants were used as donors, the incubation time was extended to one hour to allow detection of rare transconjugants.

Finally, mixes were plated at appropriate dilutions on LB-agar containing Rif (measuring recipients and transconjugants), Kn (measuring donors and transconjugants) and Rif + Kn (measuring transconjugants only).

Conjugation rates were measured as g ¼ T DRt (mL.cell -1 .h -1 ) where T, D, and R respectively indicate the density of transconjugants, donors, and recipients, and t indi- cates the incubation time.


For competition experiments (Fig 2C), stationary phase cultures of both strains were washed then mixed at a 50/50 ratio into a well-mixed population, with a varying proportion of plasmid-bearing cells for each strain, and grown from a 1/10 dilution (t 0 ).

Mixes were then fur- ther diluted 1/10 at 37°C into medium lacking antibiotics when they reached the OD (600 nm) of 1.2, and grown to stationary phase.

Finally, they were plated at appropriate dilutions on LB- agar with or without Kn selection.

Strain and plasmid frequencies were followed by identifying MG1655 red mCherry fluorescence from colonies with an Illumatool (Lightools) with 540 nm excitation and 590 nm emission filters.


For the experiments focusing on structured popula- tions (Fig 3 and Fig 6), cells were grown in Luria-Bertani (BD Difco) medium.

Antibiotics used were Kn (Sigma-Aldrich) at 50 μg/mL for selection experiments and 10 μg/mL for linkage experiments; Cm (Sigma-Aldrich) at 30 μg/mL for selection experiments and 6.25 μg/mL for linkage experiments.

Antibiotic concentration was lowered in linkage experiments in order for all cell types to grow to some extent, allowing more precise linkage measurements.


Stationary phase cultures of D + and D − strains were first washed and mixed at a 50/50 ratio (well-mixed population m), 10/90 ratio (s 1 subpopulation), and 90/10 ratio (s 2 subpopulations) of D + versus D − .

A 2.5% proportion of each strain was bearing C plasmids for selection experi- ments (Fig 3) and C or N plasmids for linkage experiments (1.25% cells bearing C and 1.25% cells bearing N, Fig 6).

Cultures were grown from a 1/10 dilution (t 0 ), then further diluted 1/10 at 37°C into medium lacking antibiotics when reaching the OD (600 nm) of 3.

Cultures were then diluted 1/10 at 30°C, and grown until stationary phase (t 1 ).

Finally, subpopulations s 1 and s 2 from the structured population (s) were pooled, and all cultures were diluted 1/100 at 30°C with or without antibiotics for the selection phase of the experiments, until stationary phase (t 2 ).

Cultures were analysed for strain and plasmid proportions by flow cytometry after fixation, as described in [6].

Data acquisition was performed on the Cochin Cytometry and Immuno- biology Facility.

For each sample, 100,000 cells were analysed using a BD LSR Fortessa cell ana- lyzer (BD Biosciences).

D + strain was identified with RFP, plasmids with YFP and GFP fluorescence (S2 Fig).


Discrimination in transfer in natural isolates.

The two datasets we analysed were Table 1 from [11] and Table 2 from [12].

In both datasets for each pair of donor and recipient strains, we computed a measure of donor ability normalized over all recipient strains tested in order to detect differences in conjugation rate to different recipients.

Let i indicate the donor strain and j the recipient strain, we compute the mean donor ability per strain, γ i , and the stan- dard deviation in the said donor ability, σ i , using logarithmic values for conjugation rates.

The normalized donor ability for a given pair is D ij ¼ g ij Àg i s i Measures of selection.

Fitness of a strain i relative to a strain j between times 0 and 1 was measured as W ij = ln(N i,1 /N i,0 )/ln(N j,1 /N j,0 ), where N represents cell densities [36].

When the cell densities were not known, the increase in number for strain i, N i,1 /N i,0 , was approximated as f i,1 /f i,0 Ã x, where f is strain i frequency in the population and x is the population increase in number.

Selection coefficients were then calculated as s = W − 1 [36].


Relatedness.

Relatedness at a locus is calculated as the linear regression coefficient con- necting an individual's allele g with the alleles of its interactants at the same locus, G [69].

For the locus controlling donor ability, we consider that g = 1 if individual is D + and 0 if it is D − , and G is the proportion of D + in the subpopulation of a focal individual.

Let d i and n i be respec- tively the number of D + and number of bacteria within subpopulation i, and d tot and n tot be respectively the number of D + and number of bacteria in the metapopulation.

Then, when sub- populations are of the same size, the relatedness of D + cells is calculated as follows:


Linkage disequilibrium quantifies the deviation from random association between alleles at different loci.

Here, we apply the concept to the association between the discrimination allele M − and the D + allele (Fig 5) and to the association between a plasmid and the D + allele (Fig 6).

For two alleles X and Y, LD X;Y ¼ F XY ÀF X F Y ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffi F X ð1ÀF X ÞF Y ð1ÀF Y Þ p , where Fxy is the frequency of individual cells bearing both X and Y alleles, and Fx and Fy are respectively the frequencies of X- and Y-bearing cells in the metapopulation.

Positive linkage indicates that X and Y are associated with each other more than what would be expected from their individ- ual frequencies.


Our simulations mimic the experimental conditions of strain growth and plasmid transfer in the same way as described in our previous work [6].

Plasmid transfer follows a mass-action law: the number of transfer events is proportional to both donor and recipient cell densities in the local population.

The probability coefficient is the transfer rate constant γ (mL.cell -1 .h -1 ).

Strains are characterized by their donor ability q that modulates effective transfer and leads to a proportional cost of donor ability for the donor cell c q .

Similarly to our experiments, we model two steps: a transfer phase (from t 0 to t 1 ), then a selection phase, in conditions where the Bacterial Altruism Promotes Horizontal Gene Transfer PLOS Biology | DOI:10.1371/journal.pbio.1002478 June 7, 2016 20 / 28 plasmid genes affect growth (from t 1 to t 2 ).

The length of the transfer phase is set to 12 h after 100-fold initial dilution from carrying capacity, and growth for the selection phase is allowed for 36 h after a second 100-fold dilution.

Equations governing changes in cell densities, pre- sented below, are common to the two steps.

N tot is the total cell density.


Donor ability with no discrimination.

In these simulations (Fig 4 and Fig 6), two incom- patible plasmids can be present.

C plasmid (encoding Cm resistance) promotes growth during the selection phase; N plasmid (parasitic plasmid, not encoding Cm resistance) does not.

D + cells have donor ability q, D − cells have no donor ability.

C plasmid-bearing cells are noted by D C , N plasmid-bearing cells are noted by D N , and plasmid-free cells are noted by D ; .


Donor ability and discrimination in transfer.

In these simulations (Fig 5), only the mutualistic C plasmid is present.

In addition to the D locus controlling donor ability, the cells are characterized by the M locus controlling restriction-modification.

M + cells do transfer indiscriminately towards M − and M + , whereas transfer from M − towards M + cells is reduced by a factor m. We assume that there is no direct cost of the M − allele to the cells.

To follow the experimental design used in Fig 2, the selection phase is not explicitly modelled here, but we Bacterial Altruism Promotes Horizontal Gene Transfer PLOS Biology | DOI:10.1371/journal.pbio.1002478 June 7, 2016 21 / 28 consider a selection at the end of the transfer phase where only plasmid-bearing cells survive.


The default parameter values used in simulations are shown in Table 1 and were estimated from our experimental data (except for the cost of donor ability in Fig 4, see below):


selection phase to prevent excessive fitness loss for donor cells, assuming a regulation prevent- ing the expression of transfer genes when densities are low and transfer unlikely.

For each parameter combination, the results were averaged over 1,000 replicate simulations.

The high number of simulations was necessary because Poisson distribution produces high variation between replicates, especially with low founding cell numbers and small initial proportion of plasmid-bearing cells.


To study linkage between donor ability and discrimination (Fig 5), competitors and initial conditions were the same as the ones for Fig 3 experiments, with each cell type ðD þ ; ; D þ p ; D À ; ; D À p Þ having an equal proportion of cells bearing M + and M − alleles.

Additionally, population structur- ing concerning the D + allele was varied by founding subpopulations s 1 and s 2 with varying D + to D − proportion (maintaining a 0.5 total proportion in s population).

With d 1 and d 2 being respec- tively D + proportion in s 1 and s 2 , we quantify the strength of population structuring by d 2 − d 1 .


In their 2016 paper, Dimitriu and colleagues [1] make use of both experimental and analytical techniques to study horizontal gene transfer and the conditions under which indirect fitness effects select for cells with high donor ability.

They report both empirically and theoretically that population bottlenecks can select for immobile genes that facilitate the spread of mobile gene elements.

Unfortunately, while Dimitriu and colleagues’ in vitro and in silico work provides solid evidence of donor selection, the mathematical model used to explain these results does not agree with the conceptual model described in the surrounding paragraphs and displays nonphysical behavior.

Here, we present a correction to the algebra, bringing it in line with the conceptual model presented; we find that selection for donor ability is no longer supported.

We then discuss the key differences between Dimitriu and colleagues’ simulation (which select for plasmid donation) and their conceptual patch model (which does not), highlighting the subtle modeling decisions that lead the 2 models to diverge.

Our sole focus in what follows is the patch model described in Dimitriu and colleagues’ paper (S1 Text [1]).

We make no attempt to discuss other possible circumstances, such as preferential sharing, as explored elsewhere in their paper.


In their patch model, Dimitriu and colleagues consider a population of bacteria with plasmid transfer rate q and plasmid susceptibility s. Each bacteria either contains some focal plasmid (p = 1) or doesn’t (p = 0).

At the start of each cycle, bacteria are split into an infinite number of patches, each with a small number of “founders” sampled from the global population.

In each patch, bacteria multiply to large numbers, and then plasmid transfer takes place.

The plasmid carriage, transfer rate, and plasmid susceptibility of founder i from patch j are denoted pi,j, qi,j, si,j, respectively.


All founding strains are assumed to grow to equal numbers during the growth stage.

Fitness effects apply during the colonization stage: Individuals have a base fitness W0, plasmid bearing individuals have an increased fitness W0 + ep, and conjugating individuals pay a cost cqqijpij.

This cost is proportional to transfer rate and is paid only by those individuals carrying plasmids before the transmission stage.

This cost is paid regardless of the presence of recipients.


Dimitriu and colleagues then assert that the fitness of individual i from patch j is the following:


Wij = W0 + ep[pij + (1 - pij)pjqjsij] - pijcqqij;


While intuitively plausible, this pj, qj term assertion runs into difficulties whenever p and q are correlated or when population numbers are low enough to create incidental correlations, as is the case during population bottlenecks—the particular case Dimitriu and colleagues wish to study.

As a concrete example of this problem, consider a patch with 2 founding cells.

Cell A contains a plasmid, and cell B contains the machinery necessary to transport it.


Naturally, nothing is going to happen, as the plasmid is stuck in a cell with no transfer apparatus.

Nonetheless, pj = 1/2 = qj and hence pjqj = 1/4, indicating a positive transfer rate in Eq 1.

Eq 1 is thus inconsistent with the physical model described.


To determine plasmid availability in a population, it is not enough to determine the average occurrence of plasmids and transfer apparatus, but instead their average co-occurrence.

Plasmid transfer takes place at a rate of (1 − pij)sij[pq]j, where [pq]j = (Σpijqij)/N, the mean of the product, as opposed to the product of the means.

Under these assumptions, we have the following:


Wi,j = W0 + ep pij + (sij/N)(1 - pij)pijqij + (sij/N)(1 - pij)Σi≠k pkjqkj - pijcqqij;


Here, we deliberately separate sij/N(1 - pij)pijqij (the “self-transfer” term) from the rest of the sum. Because (1 − pij)pij = 0, we see that, inevitably, sij/N(1 - pij)pijqij = 0.

No cell can transfer plasmids to itself, nor to any “sister cells” that originate from the same founder.

This is the critical difference brought about by [pq]j: While population bottlenecks increase relatedness in terms of q (making cooperation easier), they simultaneously increase relatedness for p, making plasmid transfer ineffective.


Assuming founding bacteria are sampled independently (as is done in Dimitriu and colleagues’ simulations), pkjqkj will be independent of qij, and we can calculate the regression coefficient β(Wij, qij) as follows:


β(Wij, qij) = Cov(Wij, qij)/Var(qij) = β(sij(1 - pij), qij)E[(N - 1)/N qkjpkj] + β(eppij, qij) - β(cqpijqij, qij);


If we also assume that qij is independent of pij and sij (a case Dimitriu and colleagues consider), this simplifies to:


β(Wij, qij) = -E(pij)cq;


The only possible effect from conjugation is negative, corresponding to the cost of conjugation.

This contrasts with the corresponding result from Dimitriu and colleagues:


β(Wij, qij) = epEj[(1 - pj)pj]β(qjsij, qij) - pijcq;


Dimitriu’s result suggests that q is favored if transfer is sufficiently efficient (Ej[(1 - pj)pj] large); however, this possibility is an artifact of the pjqj term.

When considering the more appropriate [pq]j, the only transfer term that qij is multiplied by is the self-transfer term sij/N(1 - pij)pijqij, which is, by necessity, 0.


If we drop the independent genes assumption, Eq 3 indicates that q is selected for when either β(eppij, qij) or β(sij (1 - pij), qij) compensate for the cost of conjugation; q must be sufficiently correlated with the beneficial p or s genes.

As currently presented, the patch model does not provide any mechanism for producing this correlation.

While it is possible to drop the assumption that founders are sampled independently, doing so would appear to be at odds with both the patch dispersal model described in Dimitriu and colleagues’ Supporting information (S1 Text [1]) and their simulation code (S1 Code).


Surprisingly, while Dimitriu and colleagues’ simulations do account for correlations between p and q, as described above, they nonetheless observe weak positive selection for q, contrary to Eq 4.

This apparent contradiction can be resolved by examining the differences between the 2 models in more detail: The analytic model allows only a single “conjugation event” per transfer cycle, while Dimitriu and colleagues’ simulations allow conjugation across a 36-hour time window.

In the simulations, a bacteria can both receive plasmids from an unrelated cell and subsequently donate plasmid to sister cell within a single transfer cycle.

This is not possible in the analytic model, as all conjugation takes place “simultaneously.

” Hence, we see that donor selection in spatial models is a second-order effect: Fitness benefits rely on the occurrence of multiple consecutive conjugation events.

This is suggestive of the importance of the “transcriptional burst after plasmid conjugation” [2], which has been observed experimentally, and is consistent with Dimitriu and colleagues’ observation in simulations that effect size was very small.


As shown by Dimitriu and colleagues, bacterial cooperation and spatial segregation can contribute to the evolution of plasmid transfer; however, as we show here, such results are sensitive to modeling details in particularly subtle ways.

This leads to interesting questions about how robust such effects are in real life: Are population bottlenecks and spatial structures a significant selective force in the selection and maintenance of plasmid conjugation? Or does the sensitivity of the models reflect fragility in the real-world phenomena?

These questions we leave to future authors.


In our original work [1], we demonstrated experimentally that selection can favor chromosomal alleles that confer higher plasmid donation rates, given the plasmid is beneficial and the recipient has an elevated chance of carrying the donor allele (i.e., preferential donation to kin).

Our experiments demonstrated this effect via 2 mechanisms of preferential donation: biased conjugation rates and structured populations.

We interpreted these results through the lens of kin selection theory (benefits via horizontal gene transfer to kin), supported by simulations and an analytical fitness function model.

These results hold importance by outlining that the evolution of plasmid transfer rates (a key aspect of the antibiotic resistance crisis) is not necessarily the sole product of selection on the plasmid itself and forms part of a broader series of papers from our labs investigating the sociomicrobiology of plasmids [2][3][4].


A new commentary raises concerns over our fitness function model, flagging issues with both the structure of the model and assumptions made in our analysis [5].

We stand by the general conclusions of our work but accept that our fitness function and stated analysis assumptions could be better formulated.

Our initial fitness function is heuristic in the sense it was designed to capture general processes acting on the fitness of individuals, dependent on the plasmid and donor allele status—without explicitly modeling the myriad demographic events of dispersal, reproduction, conjugation, and death that result in selective shifts across a metapopulation of cells.

Specifically, we captured the “force of infection” faced by an uninfected cell as the product of average plasmid prevalence and average donor allele prevalence in the local patch (pjqj; see commentary for notation details).

We agree with the authors that this force of infection is better phrased as the average of the product ((1/N)∑pij qij), in part because this avoids the potential pathology under limit conditions described by the authors, but also because this approach better highlights that the particular social trait in question is an “other only” cooperative trait [6], illustrated by commentary equation [2], where transmission to self and transmission to others are separated.

This separation has the important consequence of highlighting that unlike many microbial social traits where benefits accrue to a group (including self), a cooperative plasmid donor trait can only benefit other cells that lack the plasmid.

Given established costs of donation (e.g., see figure S2 in our original article), this defines our “donor” behavior as an altruistic trait, which can, therefore, only be favored by selection given nonrandom interactions among individuals (e.g., [7]).


Our experimental results outline 2 mechanisms of nonrandom interactions: preferential donation to kin and population structure.

Each of these mechanisms will generate positive covariances between focal individual qij and non-self-recipient qj donor allele states (cov(qj, qij) > 0).

The pathway via preferential donation to kin (order-of-magnitude differences according to our analyses and more recent measurements among lineages coexisting within natural populations [8]) will also likely generate positive covariances between donor and recipient abilities (cov(sij, qij) > 0).

In contrast, to arrive at the result that selection always works against plasmid donor alleles (equation [4]), the commentary makes the assumption that both of the above covariances are zero.

We suggest that the additional analyses begun by the authors are an exciting starting point to better map selection on donor alleles, under a broader array of defined assumptions on cell–cell and gene–gene structure, ideally informed by data on structures found in natural bacterial populations.


Self-monitoring of blood pressure (BP) by patients at home (HBP) is being widely used in several countries and endorsed by hypertension guidelines in Europe, US and elsewhere.

1-4 HBP monitoring shares most of the advantages of ambulatory BP monitoring (ABP), despite the fact that the two methods are applied in different daily life con- ditions.

The main clinical needs for applying these methods are the white coat and masked hypertension (MH) phenomena, which are common in both untreated and treated subjects and are missed when evaluation is exclusively based on clinic BP measurements.

1-4 Early research on ABP monitoring demonstrated its diagnostic and prognostic ability and established its role in the management of hypertension.

1 Indeed, the existence and clinical relevance of the white coat and the MH phenomena has been defined using ABP monitoring.

1,5 Despite the wide use of HBP monitoring in the community, only recently has evidence accumulated on the diagnostic 6 and prognostic 7 usefulness of the method.


On the basis of this evidence, recent European and American guidelines on HBP monitoring adopted an entirely different position and recommended for the first time that HBP should be offered to almost all subjects with elevated BP.

2,3 This recommendation appears to be stronger for the long-term follow-up of treated hypertensives, 8 in whom there is additional benefit due to the improvement of hypertension control rates when applying HBP monitoring.

9 On the other hand, the evidence on the usefulness of HBP in the initial evaluation and diagnosis is less clear, and it has been argued that ABP is more appropriate for this indication.

2 Several studies have assessed the diagnostic ability of HBP by taking ABP as reference.

6 However, they had relatively small sample size, did not always apply HBP monitoring according to guidelines and did not examine all the potential diagnoses together (sustained, white coat and MH) and in both untreated and treated subjects.

6 The aim of this study was to investigate the ability of HBP to diagnose sustained, white coat and MH by taking ABP as the reference in a large sample of untreated and treated subjects referred to a BP clinic and using a standardized protocol for all the measurement methods according to the current guidelines.


A data set of subjects assessed with clinic BP, ABP and HBP measurements was constructed using data from previous prospective studies conducted in a university hospital BP clinic from 1994 to 2007.

Participants were consecutive adults referred for elevated BP, untreated or on stable antihypertensive treat- ment for X4 weeks.

They were invited to participate in trials involving measurements of clinic BP, HBP and ABP using a standard protocol as described below.

Exclusion criteria were severe renal, cardiac or other systemic diseases, sustained arrhythmia and evidence of secondary hypertension.

The protocol of the present study was approved by the hospital scientific committee, which did not require an informed consent for this analysis of the patients' BP data and the retrospective collection of other data from patients' records.


The average number of valid clinic BP readings included in the analysis was 5.0±1.2 (range 2-6), HBP 21.3±4.2 (range 8-24) and awake ABP 42.3 ± 6.7 (range 21-60).

In the total population, clinic BP was higher than HBP (mean difference, 3.4 ± 12.9/4.6 ± 7.6 mm Hg, systolic/diastolic, Po0.001 for both) and awake ABP (mean differ- ence, 3.1 ± 14/2.8 ± 8.4 mm Hg, systolic/diastolic, for both Po0.001), whereas there is no difference between systolic HBP and awake ABP, yet diastolic HBP was lower by 1.8±7.1 mm Hg (Po0.001) (Table 2).

In treated subjects, systolic HBP was slightly higher than awake ABP, whereas the reverse was true in the untreated subjects (Table 2).


Significant associations were found between HBP and awake ABP (r¼0.63/0.76, systolic/diastolic, Po0.001 for both), clinic BP and HBP (r¼0.62/0.73, Po0.001 for both) and clinic BP and awake ABP (r¼0.53/0.69, Po0.001 for both).


The BP threshold for hypertension diagnostic was 140 mm Hg and/or 90 mm Hg (systolic/diastolic) for clinic BP and 135 mm Hg and/or 85 mm Hg for HBP and awake ABP.

1 Sustained hypertension was defined as elevated clinic and out-of-clinic BP (home or awake ambulatory).

White coat phenomenon (WCP) was defined as elevated clinic and low out-of-clinic BP in both treated and untreated subjects, and MH the reverse (low clinic and elevated out-of-clinic BP).


Participants who provided fewer than eight valid HBP readings were excluded.

HBP readings that were 450% higher than the next highest HBP reading of the individual subject were considered erroneous and were discarded, as were measurements with systolic BP o60 mm Hg or 4250 mm Hg and those with diastolic BPo30 mm Hg or 4150 mm Hg.

All HBP readings were averaged to give a single number per individual.


ABP data and additional recorded information from the report files generated by the ambulatory monitors were batch imported and organized in a relational database (Microsoft Access Office Premium 2000, Ireland) using a Visual Basic program (Microsoft Visual Basic 6 Professional Edition, Ireland 2000).

This program designed by LGR (author) for statistical analysis of ABP- derived data reads the ASCII text files generated by the ABP monitor and performs multiple data procedures and analyses, including flagging erroneous readings, valid readings and duplicate readings (repeats), and calculates the average awake and asleep ABP, according to each individual's report for in-bed and out-of-bed period.

ABP recordings with o20 valid awake readings were excluded.

Early readings taken o20 min after the monitor had been attached to subjects were also excluded because these had been taken in the clinic.

The average of the second and third clinic BP reading of the three study visits (six readings) was calculated to give clinic BP per individual.


Student's paired t-test was used for the comparison of BP measurements in the same subjects with Bonferroni's correction for multiple comparisons applied where appropriate.

We estimated that using a 5-mm Hg cutoff for clinical significant difference between systolic awake ABP and HBP, the power of a 613 subjects study sample (retrospective data set analysis) was up to 100% (a¼0.05, two-tailed), indicating an oversized study.

Student's unpaired t-test was used to compare values among subgroup of participants.

The diagnostic ability of HBP (sensitivity, specificity, positive and negative predictive value) to detect sustained, WCP and MH in the total population and separately in treated and untreated subgroups was investigated.


The k statistic was used to determine the level of agreement in diagnoses made by ABP and HBP.

Multivariable linear regression models were applied to investigate independent predictors of the ABP-HBP difference.

Binary logistic regression models were used to identify independent factors associated with WCP and MH diagnosed by HBP or ABP monitoring.

Covariates included in the models were age, gender, body mass index, systolic/diastolic clinic BP, sex, number of HBP and awake ABP readings, cardiovascular disease, diabetes, smoking, alcohol intake and treatment for hypertension.

Current smoking was defined as daily smoking or smoking cessation for o1 year and alcohol intake as consumption of any alcohol amount per week.

A probability value Po0.05 was considered statistically significant.

Analysis was performed using the PASW 18 (SPSS release 18.0; SPSS Inc., Chicago, IL, USA).


A total of 710 cases were reviewed for inclusion in the analysis and 97 (13.7%) were excluded.

Forty-eight cases were excluded due to inadequate HBP and/or ABP readings, 34 because evaluation has been performed more than once (first assessment was used), five due to treatment change during the study, five due to acute disease during the study and five due to other reasons.

A total of 613 subjects were finally included in the analysis.

Participants' characteristics are pre- sented in Table 1, for the total study population and separately for untreated and treated subjects.


In Figure 1, participants were classified according to the diagnosis of normotension (clinic and out-of-clinic), sustained hypertension (clinic and out-of-clinic), white coat and MH phenomena by HBP and awake ABP method, respectively, for the total population (1a) and in treated (1b) and untreated subjects (1c).


Sustained hypertension was diagnosed in 50% by either ABP or HBP (diagnostic agreement 89%, k¼0.79), WCP in 14 and 15%, respectively (agreement 89%, k¼0.56) and MH in 16 and 15% (agreement 88%; k¼0.52) (Figure 1; Table 3).

MH tended to be more common in treated (23% by HBP; 20% by ABP) compared with untreated subjects (10% by HBP; 12% by ABP, Po0.05/NS compared with treated), and this was also the case for WCP in treated (16% by HBP; 17% by ABP) vs. untreated subjects (12% by HBP, 13% by ABP, P¼NS compared with treated).

One-third of the treated and 10% of untreated subjects had controlled clinic and out-of-clinic BP.


By taking ABP as the reference method, the sensitivity, specificity, positive and negative predictive value of HBP in detecting sustained, WCP and MH are presented in Table 3 for the total study population and separately in untreated and treated subjects.


Among the total of 613 cases, 65 (11%) had disagreement between HBP and ABP in the diagnosis of sustained hypertension.

In 27 of these 65 cases (42%), the BP difference away from the corresponding diagnostic threshold was within 5 mm Hg, which was considered as clinically uncertain discrepancy.

Disagreement between HBP and ABP in the diagnosis of WCP was found in 65 subjects (11%) and in the diagnosis of MH in 76 (12%).

This diagnostic discrepancy in WCP was considered as clinically uncertain (BP within 5 mm Hg from diagnostic threshold) in 27 subjects (42%) and in MH in 48 (63%).

Independent predictors of the difference between HBP and awake ABP awake derived from multivariable regression models are presented in Table 4.


The same potential predictors of white coat and MH phenomena were entered in binary regression models separately for HBP and ABP.

The independent predictors of white coat and MH detected by HBP or ABP are presented in Table 5.


The main finding of this study is the consistent and substantial agreement between HBP and ABP in the diagnosis of sustained hypertension, WCP and MH in both untreated and treated subjects.

HBP appeared to have high sensitivity and specificity when tested by taking ABP monitoring as reference in the diagnosis of sustained hypertension.

Lower but still satisfactory was the sensitivity of HBP in the diagnosis of white coat and MH phenomenon whereas the specificity was 490%.


Several The investigation for potential predictors of the ABP-HBP differ- ence showed the level of systolic BP to be inversely related with the difference, suggesting that for raised BP levels ABP and HBP tend to provide similar results.

On the other hand, in lower BP, values close the diagnostic threshold disagreement is inevitably increased, since a few mm Hg difference attributed to BP variability might lead to disagreement, which is more often arithmetic (within 5 mm Hg) rather than clinically important.

A significant influence of age on the ABP-HBP difference was also shown, with elderly patients show- ing smaller difference than the younger ones.

This finding is in line with a recent meta-analysis by Ishikawa et al., 15 which showed no difference between awake ABP and HBP in older subjects, whereas in the younger HBP was lower.


The Pamela general population study provided a direct ABP/ HBP comparison in 1529 subjects and showed that of patients with white coat hypertension diagnosed by ABP 70% were detected by HBP, yet only two HBP readings were obtained in that study.

16 Smaller studies, showed diagnostic disagreement of the two methods in the detection of WCP within a range of 13-25%.

17-19 In the current study, superior agreement between the two methods in diagnosing WCP was found which as men- tioned before might be attributed to the standardized measure- ment methods according to guidelines, which fully exhausted their potential.

The sensitivity of HBP in detecting WCP was superior in the treated subgroup than the untreated and inferior to specificity values.

This trend was identified in some other smaller studies, 17,18,20 with sensitivity settled around 50% and specificity around 80%.


Regarding the MH phenomenon, in the Pamela study, 16 HBP confirmed only 57%/45% (systolic/diastolic) of patients having MH by ABP.

A cross-sectional study of 438 subjects attending a hypertension clinic also found similar proportions of masked hypertensives diagnosed by ABP or HBP (14.2 and 11.9%, respec- tively), yet among subjects with MH, there was disagreement in the diagnosis between the two methods in 23% for systolic and 30% for diastolic BP.

21 In this study, in untreated hypertensives, the diag- nostic agreement exceeded 90%, whereas in treated ones was about 80%.

As for WCP, the sensitivity of HBP was lower than specificity in the detection of MH, yet appeared to be satisfactory for clinical practice.


The determinants of white coat and MH phenomena have been intensively investigated in previous studies.

In a recent meta- analysis of 27 studies (n¼12 127), Ishikawa et al. 15 showed that increasing age, female gender and not using oscillometric device for clinic BP, predispose to WCP detecting by ABP.

In a study of 5716 subjects, white coat hypertension detected by ABP was more common among older adults, females and non-smokers.

22 These data are in line with the current findings, suggesting that female gender and non-smoking are established determinants of the WCP, irrespective of the measurement method (ABP or HBP).

This was also the case with MH, where lower clinic BP was associated with MH, irrespective of the measurement method, and smoking which is an established predictor of MH diagnosed by ABP, 23 was also a predictor of MH detected by HBP.

Taken together, the available evidence suggests that the white coat and MH phenomena have consistent clinical predictors, irrespective of the method used for their detection (ABP or HBP), which supports the view that the two methods are interchangeable.


In conclusion, HBP showed substantial diagnostic agreement with ABP in the diagnosis of hypertension.

The between-methods discrepancy may be attributable to inherent methodological differ- ences.

The imperfect reproducibility of both methods 24,25 also contributes to diagnostic discrepancy, as well as the fact that most of the BP values are close to the diagnostic thresholds, which might lead to disagreement even in cases with BP difference of a few mm Hg only.

The recent evidence from meta-analysis of outcome HBP studies, 7 together with the consistent evidence on the diagnostic ability of HBP suggest that this method should no longer be regarded as a screening test that requires confirma- tion by ABP, as has been previously proposed, 26 but as a reliable alternative to ABP.

However, ABP remains a unique tool in the assessment of nocturnal BP and the detection of non-dippers, as well as for the evaluation of short-term reading-to-reading BP variability.

Preliminary evidence suggests that novel home moni- tors can also evaluate nocturnal BP, 27 whereas medium-term day-to-day BP variability assessed by self-home measurements has been shown to predict cardiovascular risk beyond the other risk factors.

28 Given the wide availability of home monitors, their relatively low cost and the good acceptance by users, HBP monitoring should be applied in almost all subjects with elevated BP for both the initial evaluation and the long-term follow-up.


The authors declare no conflict of interest.


A recently published study by Nasothimiou et al. [ 1] concluded that daytime at-home blood pressure (BP) self-measurement is a reliable alternative to ambulatory BP monitoring (ABPM) to identify isolated-office, masked, and sustained hypertension.

Current guidelines [2] define sustained hypertension as consistently elevated clinic and ambulatory BP measurements.

Discrepancies between clinic and ABPM-derived values have been defined as 'isolated-office' hypertension, that is, elevated clinic BP but normal ambulatory BP, and 'masked' hypertension, that is, normal clinic BP but elevated ambulatory BP [2].

These guidelines also recommend the diagnosis of hypertension be based on elevated ABPM-determined awake and/or asleep BP means, using separate specified threshold values [2].

However, past studies, including that of Nasothimiou et al. [ 1], categorized individuals, as erroneously suggested in the guidelines themselves, as isolated-office hypertension or masked hypertension based solely on a comparison of clinic and awake-time BP values, whether the latter were derived from at-home self-assessments [1] or ABPM [3], and disregarding entirely the asleep BP mean, which is also recommended by the guidelines for defining hypertension.

A major limitation of all these studies [1, 3] is the process by which patients are classified; a comparison of clinic and at-home or ABPM-derived awake or even 24-h BP means would include, in each of the four resulting categories, individuals with either elevated asleep BP means and, thus, abnormally high cardiovascular disease (CVD) risk [4].


The literature indicates that the asleep BP mean better predicts CVD risk than the awake or 24-h BP means [4], and that the progressive reduction of the asleep BP during follow-up in outcome trials is the strongest predictor of decreased CVD risk, in both people with normal and elevated BP at baseline [4].

Particularly relevant are the recent findings of the Monitorización Ambulatoria para Predicción de Eventos Cardiovasculares (MAPEC) Study.

They show that the progressive decrease during follow-up in the asleep BP mean is better achieved when the entire daily dose of one or more hypertension medications is ingested at bedtime rather than in the morning, the most typical time of treatment [5-7].

The MAPEC Study was designed to investigate whether a bedtime vs. conventional morning-time hypertension therapy regimen exerts different changes in the 24-h BP profile and reduces CVD risk [4-7].

A total of 3344 subjects with baseline BP ranging from normotension to sustained hypertension according to ABPM criteria were prospectively studied throughout a 5.6-year median follow-up.

Hypertensive participants were randomized to ingest their prescribed hypertension medications upon awakening or the entire daily dose of one or more of them at bedtime.

At baseline and thereafter annually (or more frequently if hypertension treatment was adjusted), all MAPEC Study participants were first divided into categories of normal BP, isolated-office hypertension, masked hypertension and sustained hypertension by comparing their clinic BP and awake BP mean values—as customary in previous studies [3]—utilizing the recommended thresholds of 140/90 mm Hg for clinic systolic (SBP)/diastolic BP (DBP) and 135/85 mm Hg for ABPM-derived awake SBP/DBP means [2].

The subjects comprising these four categories were further divided into two additional classes according to whether they had a normal or elevated asleep SBP/DBP mean, utilizing the recommended thresholds of 120/70 mm Hg [2].

The hazard ratio (HR) of each group—adjusted according to the confounding variables of patient sex and age, diagnosis of diabetes or chronic kidney disease, sleep duration and hypertension treatment time (all medications upon awakening vs. one or more medications at bedtime)—was obtained through a Cox regression analysis using subjects with normal clinic SBP/DBP and normal awake and asleep SBP/DBP as reference.


A. Subjects with a normal asleep BP mean had an adjusted HR comparable to those of the normotensive reference group, regardless of their classification according to the awake BP mean; isolated-office (HR = 0.87, 95%CI (0.59–1.29); P = 0.501) or masked hypertension (0.71 (0.17–2.91); P = 0.629; Figure 1).

B. Subjects with an elevated asleep BP mean had a significantly higher adjusted HR than those of the normotensive reference group, regardless of their classification according to the awake BP mean; isolated-office (HR = 2.08 (1.33–3.24); P<0.001) or masked hypertension (1.77 (1.03–3.05); P = 0.039; Figure 1).

C. Subjects from the groups that were labeled either isolated-office or masked hypertension, according to the awake BP mean only, with a normal asleep BP mean had a significantly lower HR of CVD events than those with an elevated asleep BP mean (P<0.001; Figure 1).


Apart from the marked difference in CVD risk assessment when subject classification disregards the asleep BP mean, the MAPEC Study [8] indicates that the prevalence of the four considered patient categories, that is, normal BP, isolated-office, masked and sustained hypertension, is incorrect and, thus, misrepresentative of the actual clinical dimension of isolated-office and masked hypertension.

Specifically: (i) 58.2% of subjects with normal office and ambulatory awake BP, who should have been labeled with masked hypertension based on an elevated asleep BP, were in the past labeled as normotensive and, thus, mistakenly included in the reference group to calculate the comparative CVD risk of the other categories; (ii) 38.2% of subjects with normal office and elevated ambulatory awake BP, but normal asleep BP—which is indicative of low CVD risk—were labeled with masked hypertension; and (iii) 26.3% of subjects with sustained hypertension—that is, elevated office BP, normal ambulatory awake BP, and elevated asleep BP—have consistently been labeled with isolated-office hypertension.

Other reports also found attenuation by about 50% of the real prevalence of isolated-office hypertension and a significant two-fold increase in the real prevalence of masked hypertension, mainly in high-risk cohorts involving a preponderance of elderly, type 2 diabetic, chronic kidney disease, and resistant hypertension patients, who are prone to having an elevated asleep BP mean and a 24-h non-dipper/riser BP pattern [9, 10].

In conclusion, the asleep BP mean, determined by ABPM, must be used to properly identify out-of-office hypertension and cannot be omitted in the definition of isolated-office and masked hypertension.

Accordingly, these two conditions cannot be defined by comparing clinic BP with awake-time self-measurements at home, as is frequently done [3] and misleadingly recommended as an alternative to ABPM [1].


We have recently published the largest cross-sectional study to date that provides a direct comparison of ambulatory blood pressure (ABP) with home blood pressure (BP) measurements in terms of their ability to detect white coat and masked hypertension phenomena among 613 untreated or treated subjects attending a hypertension clinic [1].

Hermida et al. [ 2] criticized our paper for ignoring night time ABP measurements, and using only day time (awake) ABP for defining white and the masked hypertension phenomena.

This criticism is valid given the accumulating evidence on the prognostic ability of night time ABP, which in some studies has exceeded that of day time measurements [3].

In addition, it appears reasonable that, as far as possible, all of the information provided by 24-h-ABP monitoring should be used in diagnosing hypertension phenotypes.


We looked at the definitions applied for white coat and masked hypertension phenomena in published papers.

White coat and the masked hypertension phenomena have been extensively investigated in cross-sectional diagnostic trials.

In line with our study [1], that cross-sectional studies evaluated white coat and masked hypertension phenomena have been based almost exclusively on day time or awake ABP measurements [4, 5].

This was also the case in long-term outcome trials that assessed the prognostic significance of these phenomena, which also used day time or awake ABP measurements [6-10], with a few exceptions that used average 24-h-ABP values [11, 12].


Several guideline documents and statements by hypertension societies have provided recommendations on the evaluation of white coat and the masked hypertension phenomena in clinical practice.

The 2007 European Society of Hypertension guidelines defined white coat hypertension on the basis of day time or 24-h-ABP [13].

On the other hand, the American Heart Association recommended the use of awake ABP for the diagnosis of white coat hypertension [14, 15].

More recently, the UK National Institute for Health and Clinical Excellence, in its recommendations for the management of hypertension, defined white coat and masked hypertension on the basis of day time ABP [16].


The above mentioned data on the definitions used for white coat and masked hypertension in short-term and long-term trials, and in hypertension guidelines suggest that nocturnal ABP levels are largely ignored.

By defining white coat hypertension on the basis of day time ABP measurements, there might be cases with low day time ABP but elevated night time ABP that remain undetected.

On the other hand, by defining masked hypertension on the basis of day time measurements, there might be cases with low day time ABP but elevated night time ABP that also remain undetected.


We investigated this issue raised by Hermida et al. [ 2] by performing additional analysis of our data, with the aim of evaluating (i) the proportion of subjects who had elevated nocturnal ABP, but have been labeled as white coat hypertensive on the basis of low day time ABP and, (ii) the proportion of subjects with masked hypertension due to isolated nocturnal ABP elevation, who have been missed (classified as normotensives) because of low day time ABP.


According to our initial analysis, the white coat hypertension phenomenon was present in 88 of the 613 study subjects (14.4%) when night time (awake) ABP was ignored [1].

When night time (asleep) ABP was also evaluated, one quarter of these subjects (n = 23, 3.8%) were not classified as white coat hypertensives because of elevated night time ABP (Table 1).

As expected, these subjects tended to have higher 24-h-ABP levels than those with low day time and night time ABP or normotensives (low clinic, day time and night time ABP, Table 2).

It is important to note, however, that only 5 out of these 23 subjects had an elevated 24-h-ABP (systolic and/or diastolic >130/80 mm Hg).

Moreover, when a 5 mm Hg gray zone of diagnostic uncertainty was applied to define isolated nocturnal hypertension (5 mm Hg above the diagnostic threshold for night time ABP), only 10 subjects (1.6%) changed classification as a result of nocturnal hypertension (Table 1).


We also looked at the classification of the masked hypertension phenomenon, which was observed in 94 study subjects (15.3%) in our initial analysis that ignored night time ABP [1].

When night time ABP was taken into account, there were 27 more cases of masked hypertension due to isolated nocturnal hypertension (Table 3).

Subjects with isolated nocturnal hypertension tended to have lower 24-h-ABP levels than those with masked hypertension due to day time ABP elevation only, or day and night time ABP elevation (Table 4).

It is important to note that average 24-h ABP was normal in 24 of the 27 subjects with isolated nocturnal masked hypertension.

Moreover, when a 5 mm Hg gray zone of diagnostic uncertainty was applied to define isolated nocturnal hypertension (5 mm Hg above the diagnostic threshold for night time ABP), only seven subjects (1.1%) changed classification because of isolated nocturnal hypertension (Table 3).


The above analyses suggest that in our study taking into account night time ABP in the detection of white coat and masked hypertension phenomena, there are few cases which the diagnosis changes as a result of isolated nocturnal hypertension.

More importantly, in most of these cases, individuals have a normal average 24-h-ABP, which makes the diagnosis of ABP hypertension and the need for treatment questionable.


In our cross-sectional study, the vast majority of the participants attending a hypertension clinic had uncomplicated hypertension and low to moderate cardiovascular risk [1].

There are three important issues that cannot be investigated in our data set.

The first is the prevalence of isolated nocturnal hypertension in other populations, such as patients with established cardiovascular disease, nephropathy, diabetes or sleep apnea, in whom the prevalence of non-dipping is higher than in those with uncomplicated hypertension.

Second, we could not investigate whether individuals with isolated nocturnal hypertension have a higher cardiovascular risk than normotensives.

Third, we also could not investigate whether the selective reduction of night time BP with drug dosing before bedtime is more effective in preventing cardiovascular events than the usual morning dosing.


The International Database on Ambulatory Blood Pressure In Relation to Cardiovascular Outcomes included 8711 individuals from 10 populations, and identified 577 untreated individuals (6.4%) with isolated nocturnal hypertension (low office and day time ABP).

After a follow-up of 10.7 years, this condition was found to be associated with a higher overall mortality (hazard ratio 1.29, P = 0.045) and cardiovascular event risk (1.38, P = 0.037) [17].

Several studies in diabetic [18, 19] and non-diabetic subjects [20, 21] have suggested that elevated nocturnal ABP should be taken into account in decision making, even when day time ABP levels are low.


The usefulness of bedtime dosing of antihypertensive drug treatment aimed at improving nocturnal BP control, and thereby providing more effective protection against cardiovascular events has been inadequately investigated [22].

A recent study in hypertensive patients with nephropathy who were followed for 5.4 years showed that taking at least one antihypertensive drug at bedtime improved the control of nocturnal and 24-h-ABP and reduced the risk of cardiovascular events compared to taking all drugs in the morning [23].

On the other hand, the African American Study of Kidney Disease showed that once-daily dosing of antihypertensive treatment or the addition of drugs taken at bedtime did not significantly reduce nocturnal BP compared to morning dosing [24].


Despite the considerable number of studies that have demonstrated the prognostic relevance of nocturnal hypertension, there is still no conclusive evidence on whether a treatment strategy specifically targeting nocturnal BP can eliminate the associated cardiovascular risk [7, 22].

Although it seems reasonable that all aspects of the 24-h-BP profile should be normalized, randomized trials are still needed to demonstrate whether more complex and individualized treatment regimens can achieve more efficient cardiovascular protection than morning dosing with long-acting drugs.


Transferrin receptor-2 (TFR2) is a type II transmembrane gly- coprotein homologous to TFR1, 1 able to bind diferric-transfer- rin (holo-TF), although with lower affinity than TFR1.

In iron homeostasis TFR2 appears to have regulatory rather than transport functions, since TFR2 mutations in humans 2 and Tfr2 inactivation in mice 3-5 cause iron overload with low hepcidin.

6 TFR2 is mainly expressed in the liver 1,7 where it is essential for hepcidin control.

Its expression is up-regulated during hepatic development but is not modulated by iron; indeed TFR2 mRNA has no detectable iron-responsive elements in its untranslated regions.

8 TFR2 encodes an 801 amino acid protein with a short cytosolic tail that contains a potential internalization signal, a transmembrane domain and a large C-terminal ectodomain.

This last has a protease-associated domain, a peptidase M28- like domain and a dimerization domain with two RGD motifs, important for protein-protein interactions and for transferrin binding.


Mutations of TFR2 cause type 3 hemochromatosis: all reported mutations 2 are rare, often private.

Mutations cause loss of function and include frameshift, premature stop, small deletions and missense mutations prevalently affecting the protein C-terminus, especially the peptidase-like and the dimerization domains.

9 Binding to holo-TF stabilizes TFR2 on the cell surface 10 and this interaction redirects TFR2 towards the recycling instead of the lysosomal degradation pathway.

4 Experiments in cultured hepatoma cell lines suggest that TFR2, bound to holo-TF, may simultaneously bind HFE.

While the HFE- and the TF-binding sites on TFR1 overlap, in TFR2 they are different.

10,11 The HFE- TFR2 complex has been proposed to act as a sensor of circulat- ing iron and as an activator of hepcidin expression.

12 However, recent data suggest that the two proteins may have separate functions and their interaction is also controversial.

13 Iron over- load is more severe in Tfr2 −/− than in Hfe −/− mice and Tfr2-Hfe double knock-out mice show the most severe disease.

14 Studies in patients indicate that TFR2 plays a prominent and HFE a minor role in hepcidin activation in response to an acute increase of transferrin saturation after a single dose of oral iron.

15 As a further level of complexity, the TFR2 gene, which has two consensus sequences for the erythroid transcription factor GATA-1 in its promoter, 12 is expressed in immature ery- throid cells 16 where it is a component of the erythropoietin receptor (EPOR) complex.

17 The TFR2-EPOR association is required for the efficient transport of EPOR to the cell surface.


Although neither TFR2-hemochromatosis patients nor Tfr2 −/− mice have evident hematologic abnormalities, the erythroid progenitors from Tfr2 −/− young mice appear less sensitive to erythropoietin (EPO) and have increased serum Epo levels.

Moreover, TFR2 silencing in human erythroid progenitors delays their terminal differentiation.

17 TFR1 sheds a soluble counterpart (sTFR1), in vitro and in vivo, which is measurable in serum from normal individuals.


TFR1 is highly expressed on the surface of maturing ery- throblasts and, when unbound to holo-TF, is released into plasma in high concentrations.

This process occurs in iron deficiency anemia, in erythropoiesis expansion and in some hematologic malignancies.

19 In contrast, sTFR1 lev- els are reduced in aplastic and hypoproliferative anemias.

Although its function remains unexplained, sTFR1 has been proposed as a marker of iron deficiency and/or of total erythropoietic activity.

The shedding of sTFR1 is reg- ulated by its ligand holo-TF and, as recently shown, is mediated by the proprotein convertase subtilisin/kexin type 7 (PCSK7).

20 Interestingly, PCSK7 genetic variants are associated with sTFR1 quantitative trait in genome-wide association studies.

21 Here we characterize a previously unrecognized soluble form of TFR2 (sTFR2) that is shed from the plasma mem- brane both in transfected cell lines and in TFR2-expressing erythroid cells.


We show that the process of TFR2 release is regulated by the ligand holo-TF, a regulation lost in a TFR2 mutant (TFR2 G679A ) unable to bind the ligand.

Because of its low affinity for holo-TF, we suggest that the shedding of TFR2 signals iron deficiency simultaneously in hepatic and erythroid cells.


A TFR2 wild-type cDNA was cloned in pCMV-TAG4 vector with a FLAG-tag at the C-terminus (TFR2 WT-C-FLAG ).

TFR2 wild-type (TFR2 WT-N-FLAG ) and TFR2 G679A constructs in pcDNA3.1(+) have a FLAG-tag at the N-terminus.

A "soluble" artificial isoform of TFR2 (sTFR2*) was generated by amplification of the coding region from nucleotide 313 (Arg105) to nucleotide 2403 (Phe801) and in-frame- cloned in pSEC-TAG (B), with a MYC-HIS-tag at the C-terminus, using the following oligonucleotides: sTFR2-KpnI-fw: 5'-GGGGTACCCGAGGGTCCTGCCAGGCG- 3' sTFR2-EcoRI-rev: 5'-GGAATTCCAGAAGTTGTTATCAAT- GTTCC-3' Mammalian expressing vectors encoding for wild-type dynamin (Dyn WT ) and the dominant negative variant Dyn K44A are described elsewhere.

22 Hemojuvelin (HJV)-expressing vector and the hep- cidin promoter luciferase reporter construct (Hep-Luc) were as described previously.

23 FURIN and PCSK7 expressing vectors are described in the Online Supplementary Methods.


HeLa, HEK293, CHO-Trvb-0, the erythroleukemic cell line UT7 and the hepatoma cell lines HuH7 and Hep3B, culture conditions and reagents are described in the Online Supplementary Methods.


CD34 + cells were obtained from human donors who gave informed consent in accordance with the principles of the Declaration of Helsinki .

Approval for their use was obtained from the La Pitié-Salpétrière Hospital Institutional Ethic Committee.

CD34 + cells were purified from the peripheral blood after cyta- pheresis.

CD34 + and CD36 + cells were isolated by positive selec- tion as described in the Online Supplementary Methods.

CD36 + cells were cultured in the presence of 2 U/mL EPO, 100 ng/mL stem cell factor and 10 ng/mL interleukin-3 for up to 12 days for erythroid differentiation.


When indicated, cells were treated with different concentra- tions (0.5, 1.25, 5 and 25 mM) of human or bovine diferric-trans- ferrin (H-holo-TF and B-holo-TF, respectively) and human apo- transferrin (apo-TF) (Sigma-Aldrich, St. Louis, MO, USA) in serum-free media; erythroid cells were treated with 25 mM of human apo-TF or holo-TF.


Brefeldin-A (Sigma-Aldrich), a fungal antibiotic that alters intra- cellular trafficking by blocking protein maturation across the post- endoplasmic reticulum compartment, was used at a concentration of 100-500 ng/mL.


Procedures for pull-down of membrane and soluble TFR2, west- ern blot analysis of conditioned cell culture media and total cell lysates, and the luciferase reporter assay for the effect of sTFR2 on the hepcidin promoter are described in the Online Supplementary Methods.


UT-7 cells were suspended in binding medium (alpha-MEM containing 20 mM Hepes, 10% fetal calf serum, 0.1% sodium azide, pH 7.2).

Twenty-five microliters of the cell suspension, con- taining 4x10 6 cells, were incubated with 25 mL of conditioned medium from HEK293 cells transfected with the empty or sTFR2* expressing vectors.

Samples were equilibrated at 37°C for 60 min.

Twenty-five microliters of binding medium alone or 25 mL of a 100-fold excess of unlabeled EPO were added to the binding assay.

Then the chosen amount of 125 I-EPO was added in a volume of 25 μL and the cells were incubated for a further 30 min at 37°C.

The content of each well was carefully layered over 900 mL of a cold solution of phosphate-buffered saline and centrifuged at 4°C for 10 min at 600 g. Unbound radioactivity was counted and after three washes in phosphate-buffered saline, cell-bound radioactivity was counted in the pellet.

The non-specific binding of 125 I-EPO, deter- mined by adding a 100-fold excess of unlabeled EPO to the binding assay, was subtracted from the total binding to give the specific binding.


Two independent experiments were performed using two dif- ferent batches of 125 I-EPO and control conditioned medium or sTFR2*-containing conditioned medium from two independent experiments.


To study the cell localization and processing of TFR2, HeLa cells, which do not express endogenous TFR2 (data not shown), were transiently transfected with an expressing vec- tor that encodes for a N-FLAG tagged form of TFR2 (TFR2 WT- N-FLAG ).

Since TFR1 and other iron-related proteins present on the cell membrane release soluble forms, we investigated whether this would also occur with TFR2.


In the media of TFR2 transfected cells we identified a single band (sTFR2) of about 80 kDa, which migrated faster than the cell-associated isoforms, suggesting that it was the result of a cleavage mech- anism.

Since sTFR2 can be detected using an anti-TFR2 anti- body, recognizing residues from amino acid 150 to 250, but not with the anti-FLAG antibody when using an N-terminal flagged construct, we concluded that the cleavage occurs at the N-terminal part of the protein, close to the transmem- brane domain, as occurs for sTFR1.

24 To confirm this finding, sTFR2 from cells transfected with TFR2 WT-C-FLAG , which has a FLAG-tag at the C-terminus, was indeed detected with the anti-FLAG antibody (Figure 1A).


The size of sTFR2 is com- patible with that of a protein lacking intracellular and trans- membrane regions.

Indeed the artificial form of sTFR2 (sTFR2*), generated by cloning the TFR2 ectodomain (amino acids 105-801) downstream of the Ig k-chain leader sequence, migrates as the isoform shed from the full length TFR2 transfected cells (Figure 1A).


sTFR2 is not an artefact due to cDNA overexpression since it is also released by TFR2-expressing cells, such as the erythroleukemic cell line UT7 and human primary ery- throblasts.

Both UT7 cells and primary erythroblasts release a band of sTFR2 of approximately 80 kDa in culture media (Figure 1B), compatible with the size of sTFR2 released by TFR2-transfected cells.

In the total lysates of erythroid cells, TFR2 migrates as a doublet of about 102 and 92 kDa, as pre- viously observed.


It was previously reported that the receptor exposed on the cell surface is stabilized in the presence of holo-TF with a maximum effect at 25 mM holo-TF.

10 We confirmed the same stabilization both in transfected cells and in TFR2- competent cells.

HeLa cells transfected with TFR2 WT-C-FLAG construct were treated with human holo-TF and apo-TF (25 mM) in serum-free media and were biotinylated to label membrane proteins.

sTFR2 was pulled-down using anti- FLAG Sepharose-beads to avoid holo-TF interference with gel migration of concentrated culture media.

In these condi- tions, as a consequence of holo-TF treatment, we observed a reduction of sTFR2, mirrored by an increase in mem- brane-exposed TFR2 (Figure 2A).