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Background: Bilberries are effective in inducing clinical, endoscopic, and biochemical improvement in ulcerative colitis (UC) patients. The aim of this study was to investigate the efficacy of anthocyanin-rich extract (ACRE), the bioactive ingredient of bilberries, in a controlled clinical trial in moderate-to-severe UC. Methods: A multi-center, randomized, placebo-controlled, double-blind study with a parallel group was conducted. Initially, the study was planned for 100 patients; nevertheless, it prematurely ended due to COVID-19. Patients had moderate-to-severe active UC at screening (a Mayo score of 6-12, an endoscopic sub-score ≥ 2) and were randomized at baseline. The primary endpoint was a clinical response (week 8, a total Mayo score reduction ≥ 3 points). Fecal calprotectin (FC) and a centrally read endoscopic response were among the secondary endpoints. Results: Out of 48 patients (6 Swiss centers), 34 were randomized. Eighteen ACRE and eight placebo patients could be analyzed (per protocol set). Half (9/18) of ACRE patients and 3/8 of placebo patients responded clinically ( p = 0.278). An improvement in the Mayo score was observed in the ACRE arm (77.8% vs. 62.5% placebo). FC dropped from 1049 ± 1139 to 557 ± 756 μg/g for ACRE but not for the placebo group (947 ± 1039 to 1040 ± 1179; p = 0.035). Serious adverse events were rare. Conclusions: ACRE treatment did not yield significant superiority to the placebo. Furthermore, the placebo response was unusually high. Moreover, there was a significant calprotectin decrease at the end of treatment, indicative of ACRE efficacy in UC.

Anthocyanins (ACs) have been shown to elicit anti-inflammatory and antioxidant effects in animal models of ulcerative colitis (UC). Furthermore, we previously observed in a double-blind randomized trial in UC patients that biochemical disease activity tended to be lower in patients that were exposed to AC. Here, we report on the changes in the fecal microbiome composition in these patients upon AC exposure. UC patients received a 3 g daily dose of an AC-rich bilberry extract (ACRE) for eight weeks. We determined the microbiome composition in longitudinal stool samples from 24 patients and quantified the degree of change over time. We also correlated the relative abundances of individual microbial taxa at different timepoints to fecal concentrations of calprotectin, a proxy for inflammation. Microbiome composition did not change over time as a result of the intervention, in terms of both alpha and beta diversity. However, before the intervention, the abundance of Haemophilus parainfluenzae was positively correlated with fecal calprotectin concentrations, and this correlation persisted in placebo-treated subjects throughout the study. In contrast, the correlation between H. parainfluenzae and calprotectin vanished in ACRE-treated subjects, while the relative abundance of H. parainfluenzae did not change. Our results suggest that ACRE treatment mitigates the contribution of H. parainfluenzae to inflammation. Further research is warranted to better comprehend the role of microbial composition in response to medical therapy including AC-rich extract in UC patients.

Background: The human gut microbiome produces and consumes a variety of compounds that interact with the host and impact health. Succinate is of particular interest as it intersects with both host and microbiome metabolism. However, which gut bacteria are most responsible for the consumption of intestinal succinate is poorly understood., Results: We build upon an enrichment-based whole fecal sample culturing approach and identify two main bacterial taxa that are responsible for succinate consumption in the human intestinal microbiome, Phascolarctobacterium and Dialister. These two taxa have the hallmark of a functional guild and are strongly mutual exclusive across 21,459 fecal samples in 94 cohorts and can thus be used to assign a robust "succinotype" to an individual. We show that they differ with respect to their rate of succinate consumption in vitro and that this is associated with higher concentrations of fecal succinate. Finally, individuals suffering from inflammatory bowel disease (IBD) are more likely to have the Dialister succinotype compared to healthy subjects., Conclusions: We identified that only two bacterial genera are the key succinate consumers in human gut microbiome, despite the fact that many more intestinal bacteria encode for the succinate pathway. This highlights the importance of phenotypic assays in functionally profiling intestinal microbiota. A stratification based on "succinotype" is to our knowledge the first function-based classification of human intestinal microbiota. The association of succinotype with IBD thus builds a bridge between microbiome function and IBD pathophysiology related to succinate homeostasis. Video Abstract., (© 2024. The Author(s).)

The anaerobic cultivation of fecal microbiota is a promising approach to investigating how gut microbial communities respond to specific intestinal conditions and perturbations. Here, we describe a flexible protocol using 96-deepwell plates to cultivate stool-derived gut microbiota. Our protocol aims to address gaps in high-throughput culturing in an anaerobic chamber. We characterized the influence of the gas phase on the medium chemistry and microbial physiology and introduced a modular medium preparation process to enable the testing of several conditions simultaneously. Furthermore, we identified a medium formulation that maximized the compositional similarity of ex vivo cultures and donor microbiota while limiting the bloom of Enterobacteriaceae . Lastly, we validated the protocol by demonstrating that cultivated fecal microbiota responded similarly to dietary fibers (resistant dextrin, soluble starch) and drugs (ciprofloxacin, 5-fluorouracil) as reported in vivo. This high-throughput cultivation protocol has the potential to facilitate culture-dependent studies, accelerate the discovery of gut microbiota-diet-drug-host interactions, and pave the way to personalized microbiota-centered interventions., Competing Interests: C.M., P.B., T.W., and G.L. are or were employees of PharmaBiome AG. T.W. and C.L. are founders of PharmaBiome AG. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© The Author(s) 2024. Published by Oxford University Press on behalf of the International Society for Microbial Ecology.)

Diversity-generating retroelements (DGRs) are used by bacteria, archaea, and viruses as a targeted mutagenesis tool. Through error-prone reverse transcription, DGRs introduce random mutations at specific genomic loci, enabling rapid evolution of these targeted genes. However, the function and benefits of DGR-diversified proteins in cellular hosts remain elusive. We find that 82% of DGRs from one of the major monophyletic lineages of DGR reverse transcriptases are encoded by multicellular bacteria, which often have two or more DGR loci in their genomes. Using the multicellular purple sulfur bacterium Thiohalocapsa sp. PB-PSB1 as an example, we characterized nine distinct DGR loci capable of generating 10 282 different combinations of target proteins. With environmental metagenomes from individual Thiohalocapsa aggregates, we show that most of PB-PSB1's DGR target genes are diversified across its biogeographic range, with spatial heterogeneity in the diversity of each locus. In Thiohalocapsa PB-PSB1 and other bacteria hosting this lineage of cellular DGRs, the diversified target genes are associated with NACHT-domain anti-phage defenses and putative ternary conflict systems previously shown to be enriched in multicellular bacteria. We propose that these DGR-diversified targets act as antigen sensors that confer a form of adaptive immunity to their multicellular consortia, though this remains to be experimentally tested. These findings could have implications for understanding the evolution of multicellularity, as the NACHT-domain anti-phage systems and ternary systems share both domain homology and conceptual similarities with the innate immune and programmed cell death pathways of plants and metazoans., Competing Interests: Competing interests statement:The authors declare no competing interest.

Competing Interests: Declaration of interests D.S. is a member of the DOE Biological and Environmental Research Advisory Committee and the KBase science advisory committee. G.E.L. is an employee and shareholder of PharmaBiome AG. G.E.L. is an inventor on patent application number WO2022023458 entitled "Microbial Niche Mapping."

Horizontal gene transfer accelerates microbial evolution. The marine picocyanobacterium Prochlorococcus exhibits high genomic plasticity, yet the underlying mechanisms are elusive. Here, we report a novel family of DNA transposons-"tycheposons"-some of which are viral satellites while others carry cargo, such as nutrient-acquisition genes, which shape the genetic variability in this globally abundant genus. Tycheposons share distinctive mobile-lifecycle-linked hallmark genes, including a deep-branching site-specific tyrosine recombinase. Their excision and integration at tRNA genes appear to drive the remodeling of genomic islands-key reservoirs for flexible genes in bacteria. In a selection experiment, tycheposons harboring a nitrate assimilation cassette were dynamically gained and lost, thereby promoting chromosomal rearrangements and host adaptation. Vesicles and phage particles harvested from seawater are enriched in tycheposons, providing a means for their dispersal in the wild. Similar elements are found in microbes co-occurring with Prochlorococcus, suggesting a common mechanism for microbial diversification in the vast oligotrophic oceans., Competing Interests: Declaration of interests J.B. is an employee of Oxford Nanopore Technologies and is a shareholder and/or share option holder., (Copyright © 2022 Elsevier Inc. All rights reserved.)

The success of fecal microbiota transplants (FMT) has provided the necessary proof-of-concept for microbiome therapeutics. Yet, feces-based therapies have many associated risks and uncertainties, and hence defined microbial consortia that modify the microbiome in a targeted manner have emerged as a promising safer alternative to FMT. The development of such live biotherapeutic products has important challenges, including the selection of appropriate strains and the controlled production of the consortia at scale. Here, we report on an ecology- and biotechnology-based approach to microbial consortium construction that overcomes these issues. We selected nine strains that form a consortium to emulate the central metabolic pathways of carbohydrate fermentation in the healthy human gut microbiota. Continuous co-culturing of the bacteria produces a stable and reproducible consortium whose growth and metabolic activity are distinct from an equivalent mix of individually cultured strains. Further, we showed that our function-based consortium is as effective as FMT in counteracting dysbiosis in a dextran sodium sulfate mouse model of acute colitis, while an equivalent mix of strains failed to match FMT. Finally, we showed robustness and general applicability of our approach by designing and producing additional stable consortia of controlled composition. We propose that combining a bottom-up functional design with continuous co-cultivation is a powerful strategy to produce robust functionally designed synthetic consortia for therapeutic use.

The gut microbiome lies at the intersection between the environment and the host, with the ability to modify host responses to disease-relevant exposures and stimuli. This is evident in how enteric microbes interact with the immune system, e.g., supporting immune maturation in early life, affecting drug efficacy via modulation of immune responses, or influencing development of immune cell populations and their mediators. Many factors modulate gut ecosystem dynamics during daily life and we are just beginning to realise the therapeutic and prophylactic potential of microbiome-based interventions. These approaches vary in application, goal, and mechanisms of action. Some modify the entire community, such as nutritional approaches or faecal microbiota transplantation, while others, such as phage therapy, probiotics, and prebiotics, target specific taxa or strains. In this review, we assessed the experimental evidence for microbiome-based interventions, with a particular focus on their clinical relevance, ecological effects, and modulation of the immune system., (© 2022. The Author(s).)

Genomic data has revealed that genotypic variants of the same species, that is, strains, coexist and are abundant in natural microbial communities. However, it is not clear if strains are ecologically equivalent, and at what characteristic genetic distance they might exhibit distinct interactions and dynamics. Here, we address this problem by tracking 10 taxonomically diverse microbial communities from the pitcher plant Sarracenia purpurea in the laboratory for more than 300 generations. Using metagenomic sequencing, we reconstruct their dynamics over time and across scales, from distant phyla to closely related genotypes. We find that most strains are not ecologically equivalent and exhibit distinct dynamical patterns, often being significantly more correlated with strains from another species than their own. Although even a single mutation can affect laboratory strains, on average, natural strains typically decouple in their dynamics beyond a genetic distance of 100 base pairs. Using mathematical consumer-resource models, we show that these taxonomic patterns emerge naturally from ecological interactions between community members, but only if the interactions are coarse-grained at the level of strains, not species. Finally, by analyzing genomic differences between strains, we identify major functional hubs such as transporters, regulators, and carbohydrate-catabolizing enzymes, which might be the basis for strain-specific interactions. Our work suggests that fine-scale genetic differences in natural communities could be created and stabilized via the rapid diversification of ecological interactions between strains., Competing Interests: AG, LB, GL, LL, OC No competing interests declared, (© 2022, Goyal et al.)

Despite overall success, T cell checkpoint inhibitors for cancer treatment are still only efficient in a minority of patients. Recently, intestinal microbiota was found to critically modulate anti-cancer immunity and therapy response. Here, we identify Clostridiales members of the gut microbiota associated with a lower tumor burden in mouse models of colorectal cancer (CRC). Interestingly, these commensal species are also significantly reduced in CRC patients compared with healthy controls. Oral application of a mix of four Clostridiales strains (CC4) in mice prevented and even successfully treated CRC as stand-alone therapy. This effect depended on intratumoral infiltration and activation of CD8 + T cells. Single application of Roseburia intestinalis or Anaerostipes caccae was even more effective than CC4. In a direct comparison, the CC4 mix supplementation outperformed anti-PD-1 therapy in mouse models of CRC and melanoma. Our findings provide a strong preclinical foundation for exploring gut bacteria as novel stand-alone therapy against solid tumors., Competing Interests: Declaration of interests M.S. and M.R.S. have shares in PharmaBiome. M.S. served as Advisor for Gilead, Fresenius, Topadur, Takeda, and Celltrion, and received speaker’s honoraria from Falk Pharma and Vifor Pharma. T.W. and L. Berchtold are employees of PharmaBiome. G.E.L. is also an employee of PharmaBiome. G.R. is member of the Board of Directors of PharmaBiome. A patent related to this work has been generated (PCT/EP2021/053390). This intellectual property is entirely owned by the University of Zürich., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Protein tyrosine phosphatase nonreceptor type 2 (PTPN2) recently emerged as a promising cancer immunotherapy target. We set out to investigate the functional role of PTPN2 in the pathogenesis of human colorectal carcinoma (CRC), as its role in immune-silent solid tumors is poorly understood. We demonstrate that in human CRC, increased PTPN2 expression and activity correlated with disease progression and decreased immune responses in tumor tissues. In particular, stage II and III tumors displayed enhanced PTPN2 protein expression in tumor-infiltrating T cells, and increased PTPN2 levels negatively correlated with expression of PD-1, CTLA4, STAT1, and granzyme A. In vivo, T cell- and DC-specific PTPN2 deletion reduced tumor burden in several CRC models by promoting CD44+ effector/memory T cells, as well as CD8+ T cell infiltration and cytotoxicity in the tumor. In direct relevance to CRC treatment, T cell-specific PTPN2 deletion potentiated anti-PD-1 efficacy and induced antitumor memory formation upon tumor rechallenge in vivo. Our data suggest a role for PTPN2 in suppressing antitumor immunity and promoting tumor development in patients with CRC. Our in vivo results identify PTPN2 as a key player in controlling the immunogenicity of CRC, with the strong potential to be exploited for cancer immunotherapy.

Niche construction through interspecific interactions can condition future community states on past ones. However, the extent to which such history dependency can steer communities towards functionally different states remains a subject of active debate. Using bacterial communities collected from wild pitchers of the carnivorous pitcher plant, Sarracenia purpurea, we test the effects of history on composition and function across communities assembled in synthetic pitcher plant microcosms. We find that the diversity of assembled communities is determined by the diversity of the system at early, pre-assembly stages. Species composition is also contingent on early community states, not only because of differences in the species pool, but also because the same species have different dynamics in different community contexts. Importantly, compositional differences are proportional to differences in function, as profiles of resource use are strongly correlated with composition, despite convergence in respiration rates. Early differences in community structure can thus propagate to mature communities, conditioning their functional repertoire.

Fecal microbiota transfer (FMT) is a very efficient approach for the treatment of severe and recurring C. difficile infections. However, the beneficial effect of FMT in other disorders such as ulcerative colitis (UC) or Crohn's disease remains unclear. Furthermore, it is currently unknown how disease-associated genetic variants in donors or recipients influence the effect of FMT. We found that bacteria-transfer from wild-type (WT) donors via cohousing was efficient in inducing recovery from colitis in WT mice, but not in mice deficient in protein-tyrosine phosphatase non-receptor type 22 (PTPN22), a known risk gene for several chronic inflammatory diseases. Also cohousing of PTPN22-deficient mice with diseased WT mice failed to induce faster recovery. Our data indicate that the genetic background of the donor and the recipient influences the outcome of microbiota transfer, and offers a potential explanation why transfer of fecal microbes from some, but not all donors is efficient in UC patients.

Modern phylodynamic methods interpret an inferred phylogenetic tree as a partial transmission chain providing information about the dynamic process of transmission and removal (where removal may be due to recovery, death, or behavior change). Birth-death and coalescent processes have been introduced to model the stochastic dynamics of epidemic spread under common epidemiological models such as the SIS and SIR models and are successfully used to infer phylogenetic trees together with transmission (birth) and removal (death) rates. These methods either integrate analytically over past incidence and prevalence to infer rate parameters, and thus cannot explicitly infer past incidence or prevalence, or allow such inference only in the coalescent limit of large population size. Here, we introduce a particle filtering framework to explicitly infer prevalence and incidence trajectories along with phylogenies and epidemiological model parameters from genomic sequences and case count data in a manner consistent with the underlying birth-death model. After demonstrating the accuracy of this method on simulated data, we use it to assess the prevalence through time of the early 2014 Ebola outbreak in Sierra Leone., (© The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)

Many microorganisms secrete molecules that interact with resources outside of the cell. This includes, for example, enzymes that degrade polymers like chitin, and chelators that bind trace metals like iron. In contrast to direct uptake via the cell surface, such release strategies entail the risk of losing the secreted molecules to environmental sinks, including 'cheating' genotypes. Nevertheless, such secretion strategies are widespread, even in the well-mixed marine environment. Here, we investigate the benefits of a release strategy whose efficiency has frequently been questioned: iron uptake in the ocean by secretion of iron chelators called siderophores. We asked the question whether the release itself is essential for the function of siderophores, which could explain why this risky release strategy is widespread. We developed a reaction-diffusion model to determine the impact of siderophore release on iron uptake from the predominant iron sources in marine environments, colloidal or particulate iron, formed due to poor iron solubility. We found that release of siderophores is essential to accelerate iron uptake, as secreted siderophores transform slowly diffusing large iron particles to small, quickly diffusing iron-siderophore complexes. In addition, we found that cells can synergistically share their siderophores, depending on their distance and the size of the iron sources. Our study helps understand why release of siderophores is so widespread: even though a large fraction of siderophores is lost, the solubilization of iron through secreted siderophores can efficiently increase iron uptake, especially if siderophores are produced cooperatively by several cells. Overall, resource uptake mediated via release of molecules transforming their substrate could be essential to overcome diffusion limitation specifically in the cases of large, aggregated resources. In addition, we find that including the reaction of the released molecule with the substrate can impact the result of cooperative and competitive interactions, making our model also relevant for release-based uptake of other substrates.

Microbial communities are often highly diverse in their composition, both at a coarse-grained taxonomic level, such as genus, and at a highly resolved level, such as strains, within species. This variability can be driven by either extrinsic factors such as temperature and or by intrinsic ones, for example demographic fluctuations or ecological interactions. The relative contributions of these factors and the taxonomic level at which they influence community composition remain poorly understood, in part because of the difficulty in identifying true community replicates assembled under the same environmental parameters. Here, we address this problem using an activated granular sludge reactor in which millimetre-scale biofilm granules represent true community replicates. Differences in composition are then expected to be driven primarily by biotic factors. Using 142 shotgun metagenomes of single biofilm granules we found that, at the commonly used genus-level resolution, community replicates varied much more in their composition than would be expected from neutral assembly processes. This variation did not translate into any clear partitioning into discrete community types, that is, distinct compositional states, such as enterotypes in the human gut. However, a strong partition into community types did emerge at the strain level for the dominant organism: genotypes of Candidatus Accumulibacter that coexisted in the metacommunity (the reactor) excluded each other within community replicates (granules). Individual granule communities maintained a significant lineage structure, whereby the strain phylogeny of Accumulibacter correlated with the overall composition of the community, indicating a high potential for co-diversification among species and communities. Our results suggest that due to the high functional redundancy and competition between close relatives, alternative community types are most probably observed at the level of recently differentiated genotypes but not at higher orders of genetic resolution.

The degradation of particulate organic matter in the ocean is a central process in the global carbon cycle, the mode and tempo of which is determined by the bacterial communities that assemble on particle surfaces. Here, we find that the capacity of communities to degrade particles is highly dependent on community composition using a collection of marine bacteria cultured from different stages of succession on chitin microparticles. Different particle degrading taxa display characteristic particle half-lives that differ by ~170 h, comparable to the residence time of particles in the ocean's mixed layer. Particle half-lives are in general longer in multispecies communities, where the growth of obligate cross-feeders hinders the ability of degraders to colonize and consume particles in a dose dependent manner. Our results suggest that the microscale community ecology of bacteria on particle surfaces can impact the rates of carbon turnover in the ocean.

Intense use of antibiotics for the treatment of diseases such as tuberculosis, malaria, Staphylococcus aureus or gonorrhea has led to rapidly increasing population levels of drug resistance. This has generally necessitated a switch to new drugs and the discontinuation of older ones, after which resistance often only declines slowly or even persists indefinitely. These long-term effects are usually ascribed to low fitness costs of resistance in absence of the drug. Here we show that structure in the host population, in particular heterogeneity in number of contacts, also plays an important role in the reversion dynamics. Host contact structure acts both during the phase of intense treatment, leading to non-random distributions of the resistant strain among the infected population, and after the discontinuation of the drug, by affecting the competition dynamics resulting in a mitigation of fitness advantages. As a consequence, we observe both a lower rate of reversion and a lower probability that reversion to sensitivity on the population level occurs after treatment is stopped. Our simulations show that the impact of heterogeneity in the host structure is maximal in the biologically most plausible parameter range, namely when fitness costs of resistance are small.

Background: Parent-offspring (PO) regression is a central tool to determine the heritability of phenotypic traits; i.e., the relative extent to which those traits are controlled by genetic factors. The applicability of PO regression to viral traits is unclear because the direction of viral transmission-who is the donor (parent) and who is the recipient (offspring)-is typically unknown and viral phylogenies are sparsely sampled., Methods: We assessed the applicability of PO regression in a realistic setting using Ornstein-Uhlenbeck simulated data on phylogenies built from 11,442 Swiss HIV Cohort Study (SHCS) partial pol sequences and set-point viral load (SPVL) data from 3293 patients., Results: We found that the misidentification of donor and recipient plays a minor role in estimating heritability and showed that sparse sampling does not influence the mean heritability estimated by PO regression. A mixed-effect model approach yielded the same heritability as PO regression but could be extended to clusters of size greater than 2 and allowed for the correction of confounding effects. Finally, we used both methods to estimate SPVL heritability in the SHCS. We employed a wide range of transmission pair criteria to measure heritability and found a strong dependence of the heritability estimates to these criteria. For the most conservative genetic distance criteria, for which heritability estimates are conceptually expected to be closest to true heritability, we found estimates ranging from 32 to 46% across different bootstrap criteria. For less conservative distance criteria, we found estimates ranging down to 8%. All estimates did not change substantially after adjusting for host-demographic factors in the mixed-effect model (±2%)., Conclusions: For conservative transmission pair criteria, both PO regression and mixed-effect models are flexible and robust tools to estimate the contribution of viral genetic effects to viral traits under real-world settings. Overall, we find a strong effect of viral genetics on SPVL that is not confounded by host demographics.

Viral phylogenetic methods contribute to understanding how HIV spreads in populations, and thereby help guide the design of prevention interventions. So far, most analyses have been applied to well-sampled concentrated HIV-1 epidemics in wealthy countries. To direct the use of phylogenetic tools to where the impact of HIV-1 is greatest, the Phylogenetics And Networks for Generalized HIV Epidemics in Africa (PANGEA-HIV) consortium generates full-genome viral sequences from across sub-Saharan Africa. Analyzing these data presents new challenges, since epidemics are principally driven by heterosexual transmission and a smaller fraction of cases is sampled. Here, we show that viral phylogenetic tools can be adapted and used to estimate epidemiological quantities of central importance to HIV-1 prevention in sub-Saharan Africa. We used a community-wide methods comparison exercise on simulated data, where participants were blinded to the true dynamics they were inferring. Two distinct simulations captured generalized HIV-1 epidemics, before and after a large community-level intervention that reduced infection levels. Five research groups participated. Structured coalescent modeling approaches were most successful: phylogenetic estimates of HIV-1 incidence, incidence reductions, and the proportion of transmissions from individuals in their first 3 months of infection correlated with the true values (Pearson correlation > 90%), with small bias. However, on some simulations, true values were markedly outside reported confidence or credibility intervals. The blinded comparison revealed current limits and strengths in using HIV phylogenetics in challenging settings, provided benchmarks for future methods' development, and supports using the latest generation of phylogenetic tools to advance HIV surveillance and prevention., (© The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)

In HIV patients, the set-point viral load (SPVL) is the most widely used predictor of disease severity. Yet SPVL varies over several orders of magnitude between patients. The heritability of SPVL quantifies how much of the variation in SPVL is due to transmissible viral genetics. There is currently no clear consensus on the value of SPVL heritability, as multiple studies have reported apparently discrepant estimates. Here we illustrate that the discrepancies in estimates are most likely due to differences in the estimation methods, rather than the study populations. Importantly, phylogenetic estimates run the risk of being strongly confounded by unrealistic model assumptions. Care must be taken when interpreting and comparing the different estimates to each other., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Fitness landscapes determine the course of adaptation by constraining and shaping evolutionary trajectories. Knowledge of the structure of a fitness landscape can thus predict evolutionary outcomes. Empirical fitness landscapes, however, have so far only offered limited insight into real-world questions, as the high dimensionality of sequence spaces makes it impossible to exhaustively measure the fitness of all variants of biologically meaningful sequences. We must therefore revert to statistical descriptions of fitness landscapes that are based on a sparse sample of fitness measurements. It remains unclear, however, how much data are required for such statistical descriptions to be useful. Here, we assess the ability of regression models accounting for single and pairwise mutations to correctly approximate a complex quasi-empirical fitness landscape. We compare approximations based on various sampling regimes of an RNA landscape and find that the sampling regime strongly influences the quality of the regression. On the one hand it is generally impossible to generate sufficient samples to achieve a good approximation of the complete fitness landscape, and on the other hand systematic sampling schemes can only provide a good description of the immediate neighborhood of a sequence of interest. Nevertheless, we obtain a remarkably good and unbiased fit to the local landscape when using sequences from a population that has evolved under strong selection. Thus, current statistical methods can provide a good approximation to the landscape of naturally evolving populations., (© The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)

Effective HIV prevention requires knowledge of the structure and dynamics of the social networks across which infections are transmitted. These networks most commonly comprise chains of sexual relationships, but in some populations, sharing of contaminated needles is also an important, or even the main mechanism that connects people in the network. Whereas network data have long been collected during survey interviews, new data sources have become increasingly common in recent years, because of advances in molecular biology and the use of partner notification services in HIV prevention and treatment programmes. We review current and emerging methods for collecting HIV-related network data, as well as modelling frameworks commonly used to infer network parameters and map potential HIV transmission pathways within the network. We discuss the relative strengths and weaknesses of existing methods and models, and we propose a research agenda for advancing network analysis in HIV epidemiology. We make the case for a combination approach that integrates multiple data sources into a coherent statistical framework.

Crohn's disease (CD) and ulcerative colitis (UC) are chronic relapsing inflammatory bowel disorders (IBD), the pathogenesis of which is uncertain but includes genetic susceptibility factors, immune-mediated tissue injury and environmental influences, most of which appear to act via the gut microbiome. We hypothesized that host-microbe alterations could be used to prognostically stratify patients experiencing relapses up to four years after endoscopy. We therefore examined multiple omics data, including published and new datasets, generated from paired inflamed and non-inflamed mucosal biopsies from 142 patients with IBD (54 CD; 88 UC) and from 34 control (non-diseased) biopsies. The relapse-predictive potential of 16S rRNA gene and transcript amplicons (standing and active microbiota) were investigated along with host transcriptomics, epigenomics and genetics. While standard single-omics analysis could not distinguish between patients who relapsed and those that remained in remission within four years of colonoscopy, we did find an association between the number of flares and a patient's succinotype. Our multi-omics machine learning approach was also able to predict relapse when combining features from the microbiome and human host. Therefore multi-omics, rather than single omics, better predicts relapse within 4 years of colonoscopy, while a patient's succinotype is associated with a higher frequency of relapses.

One of the central objectives in the field of phylodynamics is the quantification of population dynamic processes using genetic sequence data or in some cases phenotypic data. Phylodynamics has been successfully applied to many different processes, such as the spread of infectious diseases, within-host evolution of a pathogen, macroevolution and even language evolution. Phylodynamic analysis requires a probability distribution on phylogenetic trees spanned by the genetic data. Because such a probability distribution is not available for many common stochastic population dynamic processes, coalescent-based approximations assuming deterministic population size changes are widely employed. Key to many population dynamic models, in particular epidemiological models, is a period of exponential population growth during the initial phase. Here, we show that the coalescent does not well approximate stochastic exponential population growth, which is typically modelled by a birth-death process. We demonstrate that introducing demographic stochasticity into the population size function of the coalescent improves the approximation for values of R0 close to 1, but substantial differences remain for large R0. In addition, the computational advantage of using an approximation over exact models vanishes when introducing such demographic stochasticity. These results highlight that we need to increase efforts to develop phylodynamic tools that correctly account for the stochasticity of population dynamic models for inference.

Set point viral load in HIV patients ranges over several orders of magnitude and is a key determinant of disease progression in HIV. A number of recent studies have reported high heritability of set point viral load implying that viral genetic factors contribute substantially to the overall variation in viral load. The high heritability is surprising given the diversity of host factors associated with controlling viral infection. Here we develop an analytical model that describes the temporal changes of the distribution of set point viral load as a function of heritability. This model shows that high heritability is the most parsimonious explanation for the observed variance of set point viral load. Our results thus not only reinforce the credibility of previous estimates of heritability but also shed new light onto mechanisms of viral pathogenesis.

One of the most important advancements in theoretical epidemiology has been the development of methods that account for realistic host population structure. The central finding is that heterogeneity in contact networks, such as the presence of 'superspreaders', accelerates infectious disease spread in real epidemics. Disease control is also complicated by the continuous evolution of pathogens in response to changing environments and medical interventions. It remains unclear, however, how population structure influences these adaptive processes. Here we examine the evolution of infectious disease in empirical and theoretical networks. We show that the heterogeneity in contact structure, which facilitates the spread of a single disease, surprisingly renders a resident strain more resilient to invasion by new variants. Our results suggest that many host contact structures suppress invasion of new strains and may slow disease adaptation. These findings are important to the natural history of disease evolution and the spread of drug-resistant strains.

Individuals invest limited resources across vital tasks such as reproduction and survival. Individuals can spread reproductive investment over their lifetime, but cues of death or reduced fitness can influence this investment. In some systems, cues of infection induce early but costly reproduction through fecundity compensation as future reproduction becomes uncertain. A key aspect of parasite biology is the delay between exposure to parasites and the onset of virulence. This creates an important window of opportunity for hosts to respond to infection. Existing models have not accounted for this delay or the costs borne by offspring. We combine a theoretical and experimental approach to assess the role of costs and the importance of delay in virulence on fecundity compensation. We find that a delay in virulence selects for plastic fecundity responses even with moderate offspring costs. We tested our model experimentally by exposing pea aphids, Acyrthosiphon pisum, to various ecologically relevant cues of infection and monitored lifetime reproduction and survival of these aphids and their offspring. Our challenges induced fecundity compensation, but we did not detect any costs in mothers or offspring. We predict that the relationship between the costs and the delay in onset of virulence, as found here, determines the success of fecundity compensation as an adaptation against parasitism.

Why some individuals develop AIDS rapidly whereas others remain healthy without treatment for many years remains a central question of HIV research. An evolutionary perspective reveals an apparent conflict between two levels of selection on the virus. On the one hand, there is rapid evolution of the virus in the host, and on the other, new observations indicate the existence of virus factors that affect the virulence of infection whose influence persists over years in infected individuals and across transmission events. Here, we review recent evidence that shows that viral genetic factors play a larger role in modulating disease severity than anticipated. We propose conceptual models that reconcile adaptive evolution at both levels of selection. Evolutionary analysis provides new insight into HIV pathogenesis.

The control, prediction, and understanding of epidemiological processes require insight into how infectious pathogens transmit in a population. The chain of transmission can in principle be reconstructed with phylogenetic methods which analyze the evolutionary history using pathogen sequence data. The quality of the reconstruction, however, crucially depends on the underlying epidemiological model used in phylogenetic inference. Until now, only simple epidemiological models have been used, which make limiting assumptions such as constant rate parameters, infinite total population size, or deterministically changing population size of infected individuals. Here, we present a novel phylogenetic method to infer parameters based on a classical stochastic epidemiological model. Specifically, we use the susceptible-infected-susceptible model, which accounts for density-dependent transmission rates and finite total population size, leading to a stochastically changing infected population size. We first validate our method by estimating epidemic parameters for simulated data and then apply it to transmission clusters from the Swiss HIV epidemic. Our estimates of the basic reproductive number R0 for the considered Swiss HIV transmission clusters are significantly higher than previous estimates, which were derived assuming infinite population size. This difference in key parameter estimates highlights the importance of careful model choice when doing phylogenetic inference. In summary, this article presents the first fully stochastic implementation of a classical epidemiological model for phylogenetic inference and thereby addresses a key aspect in ongoing efforts to merge phylogenetics and epidemiology.

The asymptomatic phase of HIV-1 infections is characterised by a stable set-point viral load (SPVL) within patients. The SPVL is a strong predictor of disease progression and shows considerable variation of multiple orders of magnitude between patients. Recent studies have found that the SPVL in donor and recipient pairs is strongly correlated indicating that the virus genotype strongly influences viral load. Viral genetic factors that increase both viral load and the replicative capacity of the virus would result in rapid within-host evolution to higher viral loads. Reconciling a stable SPVL over time with high SPVL heritability requires viral genetic factors that strongly influence SPVL but only weakly influence the competitive ability of the virus within hosts. We propose a virus trait that affects the activation of target cells, and therefore viral load, but does not confer a competitive advantage to the virus. We incorporate this virus-induced target cell activation into within- and between-host models and determine its effect on the competitive ability of virus strains and on the variation in SPVL in the host population. On the within-host level, our results show that higher rates of virus-induced target cell activation increase the SPVL and confer no selective advantage to the virus. This leads to a build up of diversity in target cell activation rates in the virus population during within-host evolution. On the between-host level, higher rates of target cell activation and therefore higher SPVL affect the transmission potential of the virus. Random selection of a new founder strain from the diverse virus population within a donor results in a standing variation in SPVL in the host population. Therefore, virus-induced target cell activation can explain the heritability of SPVL, the absence of evolution to higher viral loads during infection and a large standing variation in SPVL between hosts., (Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.)

Although fitness landscapes are central to evolutionary theory, so far no biologically realistic examples for large-scale fitness landscapes have been described. Most currently available biological examples are restricted to very few loci or alleles and therefore do not capture the high dimensionality characteristic of real fitness landscapes. Here we analyze large-scale fitness landscapes that are based on predictive models for in vitro replicative fitness of HIV-1. We find that these landscapes are characterized by large correlation lengths, considerable neutrality, and high ruggedness and that these properties depend only weakly on whether fitness is measured in the absence or presence of different antiretrovirals. Accordingly, adaptive processes on these landscapes depend sensitively on the initial conditions. While the relative extent to which mutations affect fitness on their own (main effects) or in combination with other mutations (epistasis) is a strong determinant of these properties, the fitness landscape of HIV-1 is considerably less rugged, less neutral, and more correlated than expected from the distribution of main effects and epistatic interactions alone. Overall this study confirms theoretical conjectures about the complexity of biological fitness landscapes and the importance of the high dimensionality of the genetic space in which adaptation takes place., Competing Interests: The authors have declared that no competing interests exist.

Contact structure is believed to have a large impact on epidemic spreading and consequently using networks to model such contact structure continues to gain interest in epidemiology. However, detailed knowledge of the exact contact structure underlying real epidemics is limited. Here we address the question whether the structure of the contact network leaves a detectable genetic fingerprint in the pathogen population. To this end we compare phylogenies generated by disease outbreaks in simulated populations with different types of contact networks. We find that the shape of these phylogenies strongly depends on contact structure. In particular, measures of tree imbalance allow us to quantify to what extent the contact structure underlying an epidemic deviates from a null model contact network and illustrate this in the case of random mixing. Using a phylogeny from the Swiss HIV epidemic, we show that this epidemic has a significantly more unbalanced tree than would be expected from random mixing.