Hasil untuk "Microbial ecology"

Justin Kuczynski, Jesse Stombaugh, William Walters et al.

Siddharth Chaturvedi, Ahmed El-Gazzar, Marcel van Gerven

A group of non-cooperating agents can succumb to the \emph{tragedy-of-the-commons} if all of them seek to maximize the same resource channel to improve their viability. In nature, however, groups often avoid such collapses by differentiating into distinct roles that exploit different resource channels. It remains unclear how such coordination can emerge under continual individual-level selection alone. To address this, we introduce a computational model of multi-level selection, in which group-level selection shapes a common substrate and mutation operator shared by all group members undergoing individual-level selection. We also place this process in an embodied ecology where distinct resource channels are not segregated, but coupled through the same behavioral primitives. These channels are classified as a positive-sum intake channel and a zero-sum redistribution channel. We investigate whether such a setting can give rise to role differentiation under turnover driven by birth and death. We find that in a learned ecology, both channels remain occupied at the colony level, and the collapse into a single acquisition mode is avoided. Zero-sum channel usage increases over generations despite not being directly optimized by group-level selection. Channel occupancy also fluctuates over the lifetime of a boid. Ablation studies suggest that most baseline performance is carried by the inherited behavioral basis, while the learned variation process provides a smaller but systematic improvement prior to saturation. Together, the results suggest that multi-level selection can enable groups in a common-pool setting to circumvent tragedy-of-the-commons through differentiated use of coupled channels under continual turnover.

Craig Mahlasi, Gciniwe S. Baloyi, Zaheed Gaffoor et al.

The value of Earth observation foundation models for high-impact ecological applications remains insufficiently characterized. This study is one of the first to systematically evaluate the performance, limitations and practical considerations across three common ecological use cases: forest functional trait estimation, land use and land cover mapping and peatland detection. We fine-tune two pretrained models (Prithvi-EO-2.0 and TerraMind) and benchmark them against a ResNet-101 baseline using datasets collected from open sources. Across all tasks, Prithvi-EO-2.0 and TerraMind consistently outperform the ResNet baseline, demonstrating improved generalization and transfer across ecological domains. TerraMind marginally exceeds Prithvi-EO-2.0 in unimodal settings and shows substantial gains when additional modalities are incorporated. However, performance is sensitive to divergence between downstream inputs and pretraining modalities, underscoring the need for careful dataset alignment. Results also indicate that higher-resolution inputs and more accurate pixel-level labels remain critical for capturing fine-scale ecological dynamics.

Angel Rain‐Franco, Guilherme Pavan deMoraes, Sara Beier

Abstract Coalescence describes the mixing of two entire communities, a process frequently encountered by naturally occurring microbial communities. Such coalescence events can significantly impact microbial community dynamics, and previous studies have highlighted the importance of diversity, productivity of the mixing communities, and coherence among their members in predicting post‐coalescence assembly dynamics. However, little attention has been paid to how the distribution of life history traits within the mixing communities influences the coalescence outcome. Life history traits that determine how species respond to environmental change may be especially relevant when coalescence events coincide with environmental shifts, as is typically observed when two aquatic habitats mix. In our study, we experimentally mixed communities from two aquatic sites with contrasting levels of eutrophication and disturbance histories. We incubated them for 5 days in two different media, each varying in the quality of supplied organic matter. We used metabarcoding sequencing combined with functional measurements to characterize the communities' structural characteristics and assess their performance after mixing and transplanting them into the incubation media. Our results showed that the eutrophic community, characterized by low diversity but dominated by fast‐growing generalists, strongly influenced the post‐coalescence community in terms of productivity and composition. However, diversity metrics and elevated respiration rates in the coalesced communities suggest that rare members from the specialist and highly diverse oligotrophic community were present, potentially exerting an antagonistic effect on the dominant members of the eutrophic community. Overall, our data suggest a strong impact of life histories on the community dynamics in aquatic post‐coalescence communities.

Martín A. Díaz-Viera, Arturo Ortiz-Tapia, Joaquín R. Hernández-Pérez et al.

A general 3D flow-and-transport model in porous media is derived using an axiomatic continuum-mechanics approach and implemented with the finite element method to simulate microbial enhanced oil recovery (MEOR) at core scale under laboratory conditions. The development pipeline (conceptual -> mathematical -> numerical -> computational) is detailed. The model captures clogging/declogging from biomass, changes in interfacial tension due to biosurfactant, and the resulting impact on relative permeability, capillary pressure, and residual oil saturation via a trapping-number framework. The flow model is validated (Buckley-Leverett and coreflood benchmarks); transport (microbes/nutrients/surfactant) is validated against Hendry et al. 1997 breakthrough data. Finally, the model accurately predicts a Berea-core MEOR case study using field microbes and brine, matching recovery histories with small RMS error. Owing to its generality, the framework can be extended to other EOR scenarios and constitutive laws.

Elena Plekhanova, Damien Robert, Johannes Dollinger et al.

With the exacerbation of the biodiversity and climate crises, macroecological pursuits such as global biodiversity mapping become more urgent. Remote sensing offers a wealth of Earth observation data for ecological studies, but the scarcity of labeled datasets remains a major challenge. Recently, self-supervised learning has enabled learning representations from unlabeled data, triggering the development of pretrained geospatial models with generalizable features. However, these models are often trained on datasets biased toward areas of high human activity, leaving entire ecological regions underrepresented. Additionally, while some datasets attempt to address seasonality through multi-date imagery, they typically follow calendar seasons rather than local phenological cycles. To better capture vegetation seasonality at a global scale, we propose a simple phenology-informed sampling strategy and introduce corresponding SSL4Eco, a multi-date Sentinel-2 dataset, on which we train an existing model with a season-contrastive objective. We compare representations learned from SSL4Eco against other datasets on diverse ecological downstream tasks and demonstrate that our straightforward sampling method consistently improves representation quality, highlighting the importance of dataset construction. The model pretrained on SSL4Eco reaches state of the art performance on 7 out of 8 downstream tasks spanning (multi-label) classification and regression. We release our code, data, and model weights to support macroecological and computer vision research at https://github.com/PlekhanovaElena/ssl4eco.

Taylor Whitney, Thomas Solomon, Kevin Mitchell

Microbial motion is typically analyzed by simplified models in which trajectories exhibit straight runs (perhaps with added Gaussian noise) followed by random, discrete tumbling events. We present the results of a statistical analysis of the angular dynamics for four different swimming microbes: tumbling and smooth-swimming strains of \textit{Bacillus subtilis} and two Eukaryotic algae, \textit{Tetraselmis suecica} and \textit{Euglena gracilis}. We show that the angular statistics closely resemble a Voigt profile, the convolution of a Gaussian (Lévy index $α=2$) and Lorentzian (Lévy index $α=1$) distribution. This distribution is ubiquitous for all four microbes. Rather than modeling tumbling as a discrete process, we model tumbling dynamics as a continuous process: Lévy flights in the orientational dynamics using a Lorentzian noise model. This model is analytically solvable. Each individual microbe trajectory has both stochastic behavior (noise) and varying deterministic behavior, such as helices of different sizes and frequencies and circular arcs with different radii. We model the distribution of different deterministic behavior via an ensemble theory. The deterministic behavior (e.g., circular arcs) comes from physical observations of the swimming behavior and explains many of the qualitative features in the data that cannot be explained by a pure noise model. From this theory, we estimate the strength of Lorentzian noise, the physical rotational diffusion constant, and some relevant parameters relating to the distributions of deterministic behavior. This analysis shows that in some cases Gaussian noise is not the dominant process responsible for the angular statistics following a Voigt profile.

Srikumar Sastry, Subash Khanal, Aayush Dhakal et al.

We introduce ProM3E, a probabilistic masked multimodal embedding model for any-to-any generation of multimodal representations for ecology. ProM3E is based on masked modality reconstruction in the embedding space, learning to infer missing modalities given a few context modalities. By design, our model supports modality inversion in the embedding space. The probabilistic nature of our model allows us to analyse the feasibility of fusing various modalities for given downstream tasks, essentially learning what to fuse. Using these features of our model, we propose a novel cross-modal retrieval approach that mixes inter-modal and intra-modal similarities to achieve superior performance across all retrieval tasks. We further leverage the hidden representation from our model to perform linear probing tasks and demonstrate the superior representation learning capability of our model. All our code, datasets and model will be released at https://vishu26.github.io/prom3e.

Rishi Bhandari, Adam Chun-Nin Wong, Jana C. Lee et al.

ABSTRACT Microbial control of insect pests offers promising alternatives to traditional pesticides. However, the microbial communities and factors influencing these communities within insect hosts remain poorly understood. This study examined the whole-body bacterial communities in wild Drosophila suzukii, commonly known as spotted wing Drosophila (SWD). Fly samples were collected from two farms growing wild Himalayan blackberries near blueberry crops, one blackberry farm, and one elderberry farm across four locations in the United States. Our analyses showed significant differences in microbial communities in flies across various host crops and sampling locations. We identified co-occurring bacterial genera, dominated by Gluconobacter and Morganella, and the overall microbiome was distinct from those found in laboratory-grown flies. Our findings suggest that the host crop, sex of the fly, sampling location, and their interactions play a crucial role in shaping microbial communities in SWD, indicating the influence of various ecological interactions. While no significant differences in microbiome composition were observed between male and female flies, network analysis revealed distinct sex-specific microbial co-occurrence patterns. Female flies displayed a more stable and interconnected microbial network than male flies, suggesting that sex-specific factors might influence bacterial interactions. Interestingly, the most abundant microbial taxa were not necessarily the most connected in the networks, showing that less abundant taxa may also play a significant role in shaping the fly microbiome. This study underscores the complexity of microbial ecology in SWD and highlights the necessity of considering these dynamics when developing pest management strategies in agriculture.IMPORTANCEStudies on the microbiome of spotted wing Drosophila (SWD) have primarily focused on laboratory-reared flies in controlled environments and fed artificial diets. In contrast, we examined microbial communities in wild flies from various host crops across four locations in the United States. Our findings show that these communities are distinct from those of laboratory-grown flies and are influenced by the fly’s sex, host crop, geographical location, and their interactions. Our study identifies several dominant bacterial genera across samples, suggesting that these may represent the core microbial communities in wild SWD. Given that microbial communities influence physiological activities in SWD, manipulating the microbiome may have either a positive or negative impact on insect fitness. This study enhances our understanding of microbial dynamics in understudied wild SWD populations, emphasizing the importance of these dynamics in effective integrated pest management strategies.

Nathan D. Blais, Joy M. O’Brien, Hannah Holland-Moritz et al.

Soil pore structure plays a critical role in shaping soil microbial communities, which directly influence biogeochemical cycling. A notable impact of soil pore structure on microbial communities is the inverse relationship between microbial diversity and hydrological pore connectivity, where increased hydrological pore connectivity reduces microbial diversity. Although well-studied in temperate systems, the importance of hydrological pore connectivity on soil microbial community diversity in permafrost soils is largely unknown. Although once thought to be devoid of microbial activity, more recent advances demonstrate permafrost is an active ecosystem albeit less than most unfrozen soil. Thus, these principles that govern unfrozen soils could remain impactful in permafrost. In this study, our objective was to quantify permafrost pore structure and determine if the inverse relationship between soil hydrological pore connectivity and microbial diversity persists in permafrost. To address these objectives, we analyzed eight permafrost cores from three distinct sites in Alaska. To quantify soil pore characteristics, we scanned intact permafrost using X-ray computed tomography. The Euler characteristic number was used to measure pore connectivity and serve as a proxy for potential hydrological connectivity, as direct measurement of hydrological connectivity was not possible. DNA and RNA were extracted from the scanned permafrost and analyzed via amplicon sequencing of the 16S region to quantify the total and active microbial community diversity. We found that permafrost soil shares characteristics with temperate soils despite limits in our analytical resolution (i.e., at an instrument scanning resolution of 20 µm, only macro-scale features (>75 µm) could be quantified). For example, we found that pores in the range of 75–1000 µm are the dominant pore size class and a positive relationship between total porosity and pore connectivity. Additionally, we identified pore connectivity as a potential driver of microbial diversity and provided evidence that conditions before the formation of permafrost exert a strong legacy effect on currently observed permafrost microbial diversity. These insights help to explain how soil physical structure acts to influence microbial communities in this extreme environment.

Kenneth Timmis, Paul Williams, Zeynep Ceren Karahan et al.

ABSTRACT Scientific research seeks to extend knowledge and understanding, an activity that perhaps more than any other advances society and humanity. In essence, it is the search for truth. But, because it seeks new knowledge, there is little or no benchmark for appraisal of the plausibility or validity of the immediate conclusions drawn from new information gained, no instant confirmation. For this and other reasons, the science ethos requires the highest level of rigour to ensure the highest level of probability that new findings are true, or at least the most plausible under the prevailing circumstances and state of knowledge. Research is only as good as its degree of rigour. Rigour comes through intensive and comprehensive scientific training and mentoring that teaches critical and agnostic evaluation of new results, self‐scrutiny and self‐criticism. Additional rigour comes via independent scrutiny and validation: peer review of results and interpretations submitted as publications, and peer repetition of key experiments. However, the current proliferation of publication vehicles whose business model is based on maximisation of papers published, and the revenue stream of article processing charges (APCs) they generate, is promoting an insidious degradation of rigour and quality standards of reviewing–editing practices. Such predatory practices result in the systematic degradation of research quality and its “truthfulness”. Moreover, they undermine the science ethos and threaten to create a new generation of scientists that lack this ethos. These trends will inevitably progressively erode public trust in scientists and the research ecosystem. This Editorial is a call for action to all actors, in particular leaders, in scientific research to oppose predatory practices in science dissemination—to restrict the operational space of those responsible for such practices—in order to restore and maintain research rigour and the science ethos and to prevent a downward spiral of research quality. It proposes two linked actionable solutions to the problem, one for the “pull” element of predatory practices and one for the “push” element of research ecosystem management practices, especially those promoting the publish or perish mentality, that drive authors to publish in journals with predatory practices. To counter the “pull”, we propose a solution based on the principle of prevention, rather than cure, and list a number of essential policy decisions and actions that should be taken at all levels of the science chain/cloud to achieve this. A central plank of the concept is journal accreditation, without which a journal would be ineligible for payment of APCs from public funds. For accreditation, a journal would need to convincingly demonstrate adoption of a prescribed journal code of conduct. Ideally, accreditation would also be required for inclusion in journal indexing and ranking services and bibliographic databases. To counter the “push”, we propose a top‐down imposition of a cultural change in science management that ensures merit‐based success of scientists and their careers, research best practice, improved education and mentoring of younger scientists in the science ethos and greater support of them in their careers. This must include explicit recognition of the crucial role of peer reviewing for the good health of the research enterprise, its incentivisation and appropriate appreciation of the time and effort involved. To orchestrate this change, we propose the creation of a multi‐stakeholder alliance whose brief is to develop the framework and implementation strategy for changes in the research ecosystem. This Editorial also exhorts all actors to embrace the principle of publish less, publish better and to use public funding provided by tax revenues more effectively to perpetually raise the bar of science quality, dissemination and potential to advance humanity.

Valentina Savaglia, Valentina Savaglia, Sam Lambrechts et al.

Understanding the relation between terrestrial microorganisms and edaphic factors in the Antarctic can provide insights into their potential response to environmental changes. Here we examined the composition of bacterial and micro-eukaryotic communities using amplicon sequencing of rRNA genes in 105 soil samples from the Sør Rondane Mountains (East Antarctica), differing in bedrock or substrate type and associated physicochemical conditions. Although the two most widespread taxa (Acidobacteriota and Chlorophyta) were relatively abundant in each sample, multivariate analysis and co-occurrence networks revealed pronounced differences in community structure depending on substrate type. In moraine substrates, Actinomycetota and Cercozoa were the most abundant bacterial and eukaryotic phyla, whereas on gneiss, granite and marble substrates, Cyanobacteriota and Metazoa were the dominant bacterial and eukaryotic taxa. However, at lower taxonomic level, a distinct differentiation was observed within the Cyanobacteriota phylum depending on substrate type, with granite being dominated by the Nostocaceae family and marble by the Chroococcidiopsaceae family. Surprisingly, metazoans were relatively abundant according to the 18S rRNA dataset, even in samples from the most arid sites, such as moraines in Austkampane and Widerøefjellet (“Dry Valley”). Overall, our study shows that different substrate types support distinct microbial communities, and that mineral soil diversity is a major determinant of terrestrial microbial diversity in inland Antarctic nunataks and valleys.

Luis E. Valentin-Alvarado, Sirine C. Fakra, Alexander J. Probst et al.

Abstract Background Biofilms in sulfide-rich springs present intricate microbial communities that play pivotal roles in biogeochemical cycling. We studied chemoautotrophically based biofilms that host diverse CPR bacteria and grow in sulfide-rich springs to investigate microbial controls on biogeochemical cycling. Results Sulfide springs biofilms were investigated using bulk geochemical analysis, genome-resolved metagenomics, and scanning transmission X-ray microscopy (STXM) at room temperature and 87 K. Chemolithotrophic sulfur-oxidizing bacteria, including Thiothrix and Beggiatoa, dominate the biofilms, which also contain CPR Gracilibacteria, Absconditabacteria, Saccharibacteria, Peregrinibacteria, Berkelbacteria, Microgenomates, and Parcubacteria. STXM imaging revealed ultra-small cells near the surfaces of filamentous bacteria that may be CPR bacterial episymbionts. STXM and NEXAFS spectroscopy at carbon K and sulfur L2,3 edges show that filamentous bacteria contain protein-encapsulated spherical elemental sulfur granules, indicating that they are sulfur oxidizers, likely Thiothrix. Berkelbacteria and Moranbacteria in the same biofilm sample are predicted to have a novel electron bifurcating group 3b [NiFe]-hydrogenase, putatively a sulfhydrogenase, potentially linked to sulfur metabolism via redox cofactors. This complex could potentially contribute to symbioses, for example, with sulfur-oxidizing bacteria such as Thiothrix that is based on cryptic sulfur cycling. One Doudnabacteria genome encodes adjacent sulfur dioxygenase and rhodanese genes that may convert thiosulfate to sulfite. We find similar conserved genomic architecture associated with CPR bacteria from other sulfur-rich subsurface ecosystems. Conclusions Our combined metagenomic, geochemical, spectromicroscopic, and structural bioinformatics analyses of biofilms growing in sulfide-rich springs revealed consortia that contain CPR bacteria and sulfur-oxidizing Proteobacteria, including Thiothrix, and bacteria from a new family within Beggiatoales. We infer roles for CPR bacteria in sulfur and hydrogen cycling. Video Abstract

Shuyan Xiang, Yuhong Zheng, Qingwei Zhou et al.

This study investigated the effects of nano zero-valent iron-modified biochar (nZVI@BC) as a soil amendment on potted rice growth, soil properties, and heavy metal dynamics. Seven treatments with varying amounts of soil conditioner, biochar, and nZVI@BC were applied to potted rice. Results showed that nZVI@BC application significantly improved rice agronomic traits, with the 15 g·kg⁻¹ treatment increasing the panicle formation rate by 15% and 100-grain weight by 8% compared to the control. Soil fertility was enhanced, with available phosphorus increasing from 137 to 281 mg·kg⁻¹ in the most effective treatment. Heavy metal analysis revealed that nZVI@BC application did not increase soil heavy metal content, with Cd levels remaining below 0.3 mg·kg⁻¹ across treatments. Notably, the 10 g·kg⁻¹ nZVI@BC treatment showed potential for slight Cd immobilization, reducing its concentration from 0.32 to 0.26 mg·kg⁻¹. Microbial community analysis showed that nZVI@BC altered soil microbial diversity and composition, with the 10 g·kg⁻¹ treatment resulting in the highest fungal diversity (Chao1 index: 294.219). The relative abundance of the beneficial fungal class <i>Agaricomycetes</i> increased from 40% to 55% with optimal nZVI@BC application. These findings suggest that nZVI@BC has potential as an effective soil amendment for improving rice cultivation while maintaining soil health, microbial diversity, and potentially mitigating heavy metal contamination.

Alfred M. Spormann

Kien T. Pham, Duc M. Nguyen, Duy V. Tran et al.

We have developed a mathematical model that captures stress-induced mutagenesis, a fundamental aspect of pathogenic and neoplastic evolutionary dynamics, on the fitness landscape with multiple relevant genetic traits as a high-dimensional Euclidean space. In this framework, stress-induced mutagenesis manifests as a heterogeneous diffusion process. We show how increasing mutations, and thus reducing exploitation, in a static ecology with fixed carrying capacity and maximum growth rates, can paradoxically boost population size. Remarkably, this unexpected biophysical phenomenon applies universally to any number of traits.

Matthew Asker, Lluís Hernández-Navarro, Alastair M. Rucklidge et al.

Microbial populations generally evolve in volatile environments, under conditions fluctuating between harsh and mild, e.g. as the result of sudden changes in toxin concentration or nutrient abundance. Environmental variability thus shapes the long-time population dynamics, notably by influencing the ability of different strains of microorganisms to coexist. Inspired by the evolution of antimicrobial resistance, we study the dynamics of a community consisting of two competing strains subject to twofold environmental variability. The level of toxin varies in time, favouring the growth of one strain under low drug concentration and the other strain when the toxin level is high. We also model time-changing resource abundance by a randomly switching carrying capacity that drives the fluctuating size of the community. While one strain dominates in a static environment, we show that species coexistence is possible in the presence of environmental variability. By computational and analytical means, we determine the environmental conditions under which long-lived coexistence is possible and when it is almost certain. Notably, we study the circumstances under which environmental and demographic fluctuations promote, or hinder, the strains coexistence. We also determine how the make-up of the coexistence phase and the average abundance of each strain depend on the environmental variability.

Rūta Juozaitienė, Hanno Seebens, Guillaume Latombe et al.

Aim: Spatio-temporal processes play a key role in ecology, from genes to large-scale macroecological and biogeographical processes. Existing methods studying such spatio-temporally structured data either simplify the dynamic structure or the complex interactions of ecological drivers. This paper aims to present a generic method for ecological research that allows analysing spatio-temporal patterns of biological processes at large spatial scales by including the time-varying variables that drive these dynamics. Methods: We introduce a method called relational event modelling (REM), which relies on temporal interaction dynamics, that encode sequences of relational events connecting a sender node to a recipient node at a specific point in time. We apply REM to the spread of alien species around the globe between 1880 and 2005, following accidental or deliberate introductions into geographical regions outside of their native range. In this context, a relational event represents the new occurrence of an alien species given its former distribution. Results: The application of REM to the first reported invasions of 4835 established alien species outside of their native ranges from four major taxonomic groups enables us to unravel the main drivers of the dynamics of the spread of invasive alien species. Combining the alien species first records data with other spatio-temporal information enables us to discover which factors have been responsible for the spread of species across the globe. Besides the usual drivers of species invasions, such as trade, land use and climatic conditions, we also find evidence for species-interconnectedness in alien species spread. Conclusions: REM offer the capacity to account for the temporal sequences of ecological events such as biological invasions and to investigate how relationships between these events and potential drivers change over time.

Spandita Pal, Gorati Vani, Pragnya Rao Donthineni et al.

Purpose: To understand the bacterial microbiome changes associated with Sjogren's syndrome (SS) and non-Sjogren's syndrome (NSS) aqueous-deficient dry eyes compared to healthy eyes. Methods: Bacterial microbiome was generated from the deoxyribonucleic acid of tear film samples in healthy (n = 33), SS (n = 17), and NSS (n = 28) individuals. Sequencing of the V3-V4 region of the 16S rRNA gene was performed on the Illumina HiSeq2500 platform. Quantitative Insights Into Microbial Ecology (QIIME) pipeline was used to assign taxa to sequences. Statistical analysis was performed in R to assess the alpha diversity and beta diversity indices. Significant changes between the healthy, SS, and NSS cohorts were depicted by principal coordinate analysis (PCoA), differential abundance, and network analysis. Results: Tear microbiome was generated in healthy, SS, and NSS samples. Phyla Actinobacteria, Firmicutes, and Bacteroidetes showed significant changes in SS and NSS compared to healthy. Genera Lactobacillus and Bacillus were predominantly present in all samples. PCoA and heat map analysis showed distinct clusters for SS and NSS from the healthy cohort. Genera Prevotella, Coriobacteriaceae UCG-003, Enterococcus, Streptomyces, Rhodobacter, Ezakiella, and Microbacterium significantly increased in abundance in SS and NSS compared to a healthy cohort. Bacteria–bacteria interaction in SS, NSS, and healthy cohorts was predicted by CoNet network analysis. This analysis predicted a major hub of interaction for the pro-inflammatory bacterium Prevotella in the SS and NSS cohorts. Conclusion: The results of the study indicate significant changes in the phyla and genera in SS and NSS compared to healthy. Both discriminative analysis and network analysis indicated a possible association of predominant pro-inflammatory bacteria with SS and NSS.

G. Boza, G. Barabás, I. Scheuring et al.

Abstract Syntrophic cooperation among prokaryotes is ubiquitous and diverse. It relies on unilateral or mutual aid that may be both catalytic and metabolic in nature. Hypotheses of eukaryotic origins claim that mitochondrial endosymbiosis emerged from mutually beneficial syntrophy of archaeal and bacterial partners. However, there are no other examples of prokaryotic syntrophy leading to endosymbiosis. One potential reason is that when externalized products become public goods, they incite social conflict due to selfish mutants that may undermine any mutualistic interactions. To rigorously evaluate these arguments, here we construct a general mathematical framework of the ecology and evolution of different types of syntrophic partnerships. We do so both in a general microbial and in a eukaryogenetic context. Studying the case where partners cross-feed on each other’s self-inhibiting waste, we show that cooperative partnerships will eventually dominate over selfish mutants. By contrast, systems where producers actively secrete enzymes that cross-facilitate their partners’ resource consumption are not robust against cheaters over evolutionary time. We conclude that cross-facilitation is unlikely to provide an adequate syntrophic origin for endosymbiosis, but that cross-feeding mutualisms may indeed have played that role.