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Department of Plant Pathology and Microbiology
The Robert H. Smith Faculty of Agriculture, Food & Environment
The Hebrew University of Jerusalem

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Rehovot 76100 
ISRAEL

Tel: 08-9489219
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Publications

2021
Meroz, N. ; Tovi, N. ; Sorokin, Y. ; Friedman, J. Community composition of microbial microcosms follows simple assembly rules at evolutionary timescales. 2021, 12, 2891. Publisher's VersionAbstract
Managing and engineering microbial communities relies on the ability to predict their composition. While progress has been made on predicting compositions on short, ecological timescales, there is still little work aimed at predicting compositions on evolutionary timescales. Therefore, it is still unknown for how long communities typically remain stable after reaching ecological equilibrium, and how repeatable and predictable are changes when they occur. Here, we address this knowledge gap by tracking the composition of 87 two- and three-species bacterial communities, with 3–18 replicates each, for ~400 generations. We find that community composition typically changed during evolution, but that the composition of replicate communities remained similar. Furthermore, these changes were predictable in a bottom-up approach—changes in the composition of trios were consistent with those that occurred in pairs during coevolution. Our results demonstrate that simple assembly rules can hold even on evolutionary timescales, suggesting it may be possible to forecast the evolution of microbial communities.
2019
Kokou, F. ; Sasson, G. ; Friedman, J. ; Eyal, S. ; Ovadia, O. ; Harpaz, S. ; Cnaani, A. ; Mizrahi, I. Core gut microbial communities are maintained by beneficial interactions and strain variability in fish. Nature Microbiology 2019, 4 2456-2465. Publisher's VersionAbstract
The term core microbiome describes microbes that are consistently present in a particular habitat. If the conditions in that habitat are highly variable, core microbes may also be considered to be ecological generalists. However, little is known about whether metabolic competition and microbial interactions influence the ability of some microbes to persist in the core microbiome while others cannot. We investigated microbial communities at three sites in the guts of European seabass under four dietary conditions. We identified generalist core microbial populations in each gut site that are shared across fish, present under multiple diets and persistent over time. We found that core microbes tend to show synergistic growth in co-culture, and low levels of predicted and validated metabolic competition. Within core microbial species, we found high levels of intraspecific variability and strain-specific habitat specialization. Thus, both intraspecific variability and interspecific facilitation may contribute to the ecological stability of the animal core microbiome. © 2019, The Author(s), under exclusive licence to Springer Nature Limited.
Kehe, J. ; Kulesa, A. ; Ortiz, A. ; Ackerman, C. M. ; Thakku, S. G. ; Sellers, D. ; Kuehn, S. ; Gore, J. ; Friedman, J. ; Blainey, P. C. Massively parallel screening of synthetic microbial communities. Proceedings of the National Academy of Sciences of the United States of America 2019, 116, 12804-12809. Publisher's VersionAbstract
Microbial communities have numerous potential applications in biotechnology, agriculture, and medicine. Nevertheless, the limited accuracy with which we can predict interspecies interactions and environmental dependencies hinders efforts to rationally engineer beneficial consortia. Empirical screening is a complementary approach wherein synthetic communities are combinatorially constructed and assayed in high throughput. However, assembling many combinations of microbes is logistically complex and difficult to achieve on a timescale commensurate with microbial growth. Here, we introduce the kChip, a droplets-based platform that performs rapid, massively parallel, bottom-up construction and screening of synthetic microbial communities. We first show that the kChip enables phenotypic characterization of microbes across environmental conditions. Next, in a screen of ∼100,000 multispecies communities comprising up to 19 soil isolates, we identified sets that promote the growth of the model plant symbiont Herbaspirillum frisingense in a manner robust to carbon source variation and the presence of additional species. Broadly, kChip screening can identify multispecies consortia possessing any optically assayable function, including facilitation of biocontrol agents, suppression of pathogens, degradation of recalcitrant substrates, and robustness of these functions to perturbation, with many applications across basic and applied microbial ecology. © 2019 National Academy of Sciences. All rights reserved.
Abreu, C. I. ; Friedman, J. ; Andersen Woltz, V. L. ; Gore, J. Mortality causes universal changes in microbial community composition. Nature Communications 2019, 10. Publisher's VersionAbstract
All organisms are sensitive to the abiotic environment, and a deteriorating environment can cause extinction. However, survival in a multispecies community depends upon interactions, and some species may even be favored by a harsh environment that impairs others, leading to potentially surprising community transitions as environments deteriorate. Here we combine theory and laboratory microcosms to predict how simple microbial communities will change under added mortality, controlled by varying dilution. We find that in a two-species coculture, increasing mortality favors the faster grower, confirming a theoretical prediction. Furthermore, if the slower grower dominates under low mortality, the outcome can reverse as mortality increases. We find that this tradeoff between growth and competitive ability is prevalent at low dilution, causing outcomes to shift dramatically as dilution increases, and that these two-species shifts propagate to simple multispecies communities. Our results argue that a bottom-up approach can provide insight into how communities change under stress. © 2019, The Author(s).
2018
Smillie, C. S. ; Sauk, J. ; Gevers, D. ; Friedman, J. ; Sung, J. ; Youngster, I. ; Hohmann, E. L. ; Staley, C. ; Khoruts, A. ; Sadowsky, M. J. ; et al. Strain Tracking Reveals the Determinants of Bacterial Engraftment in the Human Gut Following Fecal Microbiota Transplantation. Cell Host Microbe 2018, 23, 229-240.e5.Abstract
Fecal microbiota transplantation (FMT) from healthy donor to patient is a treatment for microbiome-associated diseases. Although the success of FMT requires donor bacteria to engraft in the patient's gut, the forces governing engraftment in humans are unknown. Here we use an ongoing clinical experiment, the treatment of recurrent Clostridium difficile infection, to uncover the rules of engraftment in humans. We built a statistical model that predicts which bacterial species will engraft in a given host, and developed Strain Finder, a method to infer strain genotypes and track them over time. We find that engraftment can be predicted largely from the abundance and phylogeny of bacteria in the donor and the pre-FMT patient. Furthermore, donor strains within a species engraft in an all-or-nothing manner and previously undetected strains frequently colonize patients receiving FMT. We validated these findings for metabolic syndrome, suggesting that the same principles of engraftment extend to other indications.
Gore, J. ; Higgins, L. ; Friedman, J. Using pair-wise competitive outcomes to understand microbial communities. In APS March Meeting Abstracts; APS March Meeting Abstracts; 2018; Vol. 2018, pp. H49.010.
2017
Friedman, J. ; Gore, J. Ecological systems biology: The dynamics of interacting populations. Current Opinion in Systems Biology 2017, 1 114 - 121. Publisher's VersionAbstract
Ecological systems biology integrates theory and experiments in simple laboratory systems to study how interactions between individuals determine the emergent properties of complex biological communities. This approach reveals parallels between ecological dynamics that result from interactions between populations, and evolutionary dynamics which result from analogous interactions within a population. Tractable microbial systems enable systematic testing of theoretical predications, and identification of novel principles. Notable examples include using a cooperatively growing yeast population to detect theoretically predicted early-warning indicators preceding sudden population collapse, validating predicted spatial expansion patterns using two yeast strains which exchange essential metabolites, and the recent realization that coevolution of predators and prey qualitatively alters the oscillations that are observed in a rotifer-algae system.
Friedman, J. ; Higgins, L. M. ; Gore, J. Community structure follows simple assembly rules in microbial microcosms. 2017, 1 0109. Publisher's VersionAbstract
Microorganisms typically form diverse communities of interacting species, whose activities have tremendous impact on the plants, animals and humans they associate with. The ability to predict the structure of these complex communities is crucial to understanding and managing them. Here, we propose a simple, qualitative assembly rule that predicts community structure from the outcomes of competitions between small sets of species, and experimentally assess its predictive power using synthetic microbial communities composed of up to eight soil bacterial species. Nearly all competitions resulted in a unique, stable community, whose composition was independent of the initial species fractions. Survival in three-species competitions was predicted by the pairwise outcomes with an accuracy of ~90%. Obtaining a similar level of accuracy in competitions between sets of seven or all eight species required incorporating additional information regarding the outcomes of the three-species competitions. Our results demonstrate experimentally the ability of a simple bottom-up approach to predict community structure. Such an approach is key for anticipating the response of communities to changing environments, designing interventions to steer existing communities to more desirable states and, ultimately, rationally designing communities de novo.
Xiao, Y. ; Angulo, M. T. ; Friedman, J. ; Waldor, M. K. ; Weiss, S. T. ; Liu, Y. - Y. Mapping the ecological networks of microbial communities. 2017, 8 2042. Publisher's VersionAbstract
Mapping the ecological networks of microbial communities is a necessary step toward understanding their assembly rules and predicting their temporal behavior. However, existing methods require assuming a particular population dynamics model, which is not known a priori. Moreover, those methods require fitting longitudinal abundance data, which are often not informative enough for reliable inference. To overcome these limitations, here we develop a new method based on steady-state abundance data. Our method can infer the network topology and inter-taxa interaction types without assuming any particular population dynamics model. Additionally, when the population dynamics is assumed to follow the classic Generalized Lotka–Volterra model, our method can infer the inter-taxa interaction strengths and intrinsic growth rates. We systematically validate our method using simulated data, and then apply it to four experimental data sets. Our method represents a key step towards reliable modeling of complex, real-world microbial communities, such as the human gut microbiota.
2016
Bashan, A. ; Gibson, T. E. ; Friedman, J. ; Carey, V. J. ; Weiss, S. T. ; Hohmann, E. L. ; Liu, Y. - Y. Universality of human microbial dynamics. 2016, 534, 259 - 262. Publisher's VersionAbstract
A new computational method to characterize the dynamics of human-associated microbial communities is applied to data from two large-scale metagenomic studies, and suggests that gut and mouth microbiomes of healthy individuals are subjected to universal (that is, host-independent) dynamics, whereas skin microbiomes are shaped by the host environment; the method paves the way to designing general microbiome-based therapies.
Weiss, S. ; Van Treuren, W. ; Lozupone, C. ; Faust, K. ; Friedman, J. ; Deng, Y. ; Xia, L. C. ; Xu, Z. Z. ; Ursell, L. ; Alm, E. J. ; et al. Correlation detection strategies in microbial data sets vary widely in sensitivity and precision. 2016, 10, 1669 - 1681. Publisher's VersionAbstract
Disruption of healthy microbial communities has been linked to numerous diseases, yet microbial interactions are little understood. This is due in part to the large number of bacteria, and the much larger number of interactions (easily in the millions), making experimental investigation very difficult at best and necessitating the nascent field of computational exploration through microbial correlation networks. We benchmark the performance of eight correlation techniques on simulated and real data in response to challenges specific to microbiome studies: fractional sampling of ribosomal RNA sequences, uneven sampling depths, rare microbes and a high proportion of zero counts. Also tested is the ability to distinguish signals from noise, and detect a range of ecological and time-series relationships. Finally, we provide specific recommendations for correlation technique usage. Although some methods perform better than others, there is still considerable need for improvement in current techniques.
Preheim, S. P. ; Olesen, S. W. ; Spencer, S. J. ; Materna, A. ; Varadharajan, C. ; Blackburn, M. ; Friedman, J. ; Rodríguez, J. ; Hemond, H. ; Alm, E. J. Surveys, simulation and single-cell assays relate function and phylogeny in a lake ecosystem. 2016, 1 16130. Publisher's VersionAbstract
Much remains unknown about what drives microbial community structure and diversity. Highly structured environments might offer clues. For example, it may be possible to identify metabolically similar species as groups of organisms that correlate spatially with the geochemical processes they carry out. Here, we use a 16S ribosomal RNA gene survey in a lake that has chemical gradients across its depth to identify groups of spatially correlated but phylogenetically diverse organisms. Some groups had distributions across depth that aligned with the distributions of metabolic processes predicted by a biogeochemical model, suggesting that these groups performed biogeochemical functions. A single-cell genetic assay showed, however, that the groups associated with one biogeochemical process, sulfate reduction, contained only a few organisms that have the genes required to reduce sulfate. These results raise the possibility that some of these spatially correlated groups are consortia of phylogenetically diverse and metabolically different microbes that cooperate to carry out geochemical functions.
Pérez-Escudero, A. ; Friedman, J. ; Gore, J. Preferential interactions promote blind cooperation and informed defection. Proceedings of the National Academy of Sciences 2016, 113, 13995. Publisher's VersionAbstract
Humans often behave in seemingly irrational ways. A common instance of such perplexing behavior is that we typically care about how and why people chose their actions, rather than caring only about the actions themselves. For example, when people agree to do us a favor, we prefer them to do so directly, rather than to first gather all the relevant information. Using game theory, we show that this preference may in fact be rational: The decision-making process often reveals hidden preferences of the decision maker, which can become relevant in a future interaction. This work elucidates the conditions that make caring about motivations beneficial and makes predictions regarding the real-world situations in which it is expected to occur.It is common sense that costs and benefits should be carefully weighed before deciding on a course of action. However, we often disapprove of people who do so, even when their actual decision benefits us. For example, we prefer people who directly agree to do us a favor over those who agree only after securing enough information to ensure that the favor will not be too costly. Why should we care about how people make their decisions, rather than just focus on the decisions themselves? Current models show that punishment of information gathering can be beneficial because it forces blind decisions, which under some circumstances enhances cooperation. Here we show that aversion to information gathering can be beneficial even in the absence of punishment, due to a different mechanism: preferential interactions with reliable partners. In a diverse population where different people have different—and unknown—preferences, those who seek additional information before agreeing to cooperate reveal that their preferences are close to the point where they would choose not to cooperate. Blind cooperators are therefore more likely to keep cooperating even if conditions change, and aversion to information gathering helps to interact preferentially with them. Conversely, blind defectors are more likely to keep defecting in the future, leading to a preference for informed defectors over blind ones. Both mechanisms—punishment to force blind decisions and preferential interactions—give qualitatively different predictions, which may enable experimental tests to disentangle them in real-world situations.