Hasil untuk "Microbial ecology"

Samir K. Banerjee, Klaus Schlaeppi, M. V. D. van der Heijden

Kassem Makki, E. Deehan, J. Walter et al.

Food is a primordial need for our survival and well-being. However, diet is not only essential to maintain human growth, reproduction, and health, but it also modulates and supports the symbiotic microbial communities that colonize the digestive tract-the gut microbiota. Type, quality, and origin of our food shape our gut microbes and affect their composition and function, impacting host-microbe interactions. In this review, we will focus on dietary fibers, which interact directly with gut microbes and lead to the production of key metabolites such as short-chain fatty acids, and discuss how dietary fiber impacts gut microbial ecology, host physiology, and health. Hippocrates' notion "Let food be thy medicine and medicine be thy food" remains highly relevant millennia later, but requires consideration of how diet can be used for modulation of gut microbial ecology to promote health.

P. Menzel, K. Ng, A. Krogh

Metagenomics emerged as an important field of research not only in microbial ecology but also for human health and disease, and metagenomic studies are performed on increasingly larger scales. While recent taxonomic classification programs achieve high speed by comparing genomic k-mers, they often lack sensitivity for overcoming evolutionary divergence, so that large fractions of the metagenomic reads remain unclassified. Here we present the novel metagenome classifier Kaiju, which finds maximum (in-)exact matches on the protein-level using the Burrows–Wheeler transform. We show in a genome exclusion benchmark that Kaiju classifies reads with higher sensitivity and similar precision compared with current k-mer-based classifiers, especially in genera that are underrepresented in reference databases. We also demonstrate that Kaiju classifies up to 10 times more reads in real metagenomes. Kaiju can process millions of reads per minute and can run on a standard PC. Source code and web server are available at http://kaiju.binf.ku.dk. Here, Anders Krogh and colleagues describe Kaiju, a metagenome taxonomic classification program that uses maximum (in-)exact matches on the protein-level to account for evolutionary divergence. The authors show that Kaiju performs faster and is more sensitive compared with existing algorithms and can be used on a standard computer.

Paul J. McMurdie, S. Holmes

Background The analysis of microbial communities through DNA sequencing brings many challenges: the integration of different types of data with methods from ecology, genetics, phylogenetics, multivariate statistics, visualization and testing. With the increased breadth of experimental designs now being pursued, project-specific statistical analyses are often needed, and these analyses are often difficult (or impossible) for peer researchers to independently reproduce. The vast majority of the requisite tools for performing these analyses reproducibly are already implemented in R and its extensions (packages), but with limited support for high throughput microbiome census data. Results Here we describe a software project, phyloseq, dedicated to the object-oriented representation and analysis of microbiome census data in R. It supports importing data from a variety of common formats, as well as many analysis techniques. These include calibration, filtering, subsetting, agglomeration, multi-table comparisons, diversity analysis, parallelized Fast UniFrac, ordination methods, and production of publication-quality graphics; all in a manner that is easy to document, share, and modify. We show how to apply functions from other R packages to phyloseq-represented data, illustrating the availability of a large number of open source analysis techniques. We discuss the use of phyloseq with tools for reproducible research, a practice common in other fields but still rare in the analysis of highly parallel microbiome census data. We have made available all of the materials necessary to completely reproduce the analysis and figures included in this article, an example of best practices for reproducible research. Conclusions The phyloseq project for R is a new open-source software package, freely available on the web from both GitHub and Bioconductor.

R. Burns, J. DeForest, Juergen Marxsen et al.

C. Huttenhower, D. Gevers, R. Knight et al.

Studies of the human microbiome have revealed that even healthy individuals differ remarkably in the microbes that occupy habitats such as the gut, skin and vagina. Much of this diversity remains unexplained, although diet, environment, host genetics and early microbial exposure have all been implicated. Accordingly, to characterize the ecology of human-associated microbial communities, the Human Microbiome Project has analysed the largest cohort and set of distinct, clinically relevant body habitats so far. We found the diversity and abundance of each habitat’s signature microbes to vary widely even among healthy subjects, with strong niche specialization both within and among individuals. The project encountered an estimated 81–99% of the genera, enzyme families and community configurations occupied by the healthy Western microbiome. Metagenomic carriage of metabolic pathways was stable among individuals despite variation in community structure, and ethnic/racial background proved to be one of the strongest associations of both pathways and microbes with clinical metadata. These results thus delineate the range of structural and functional configurations normal in the microbial communities of a healthy population, enabling future characterization of the epidemiology, ecology and translational applications of the human microbiome.

P. Turnbaugh, F. Bäckhed, L. Fulton et al.

T. Battin, L. Kaplan, S. Findlay et al.

R. Amann, B. Fuchs

J. Walter, R. Ley

J. Bever, Thomas G. Platt, Elise R Morton

Giuseppe Paolo, Jamieson Warner, Hormoz Shahrzad et al.

As autonomous agents increasingly operate in real-world digital ecosystems, understanding how they coordinate, form institutions, and accumulate shared culture becomes both a scientific and practical priority. This paper introduces TerraLingua, a persistent multi-agent ecology designed to study open-ended dynamics in such systems. Unlike prior large language model simulations with static or consequence-free environments, TerraLingua imposes resource constraints and limited lifespans for the agents. As a result, agents create artifacts that persist beyond individuals, shaping future interactions and selection pressures. To characterize the dynamics, an AI Anthropologist systematically analyzes agent behavior, group structure, and artifact evolution. Across experimental conditions, the results reveal the emergence of cooperative norms, division of labor, governance attempts, and branching artifact lineages consistent with cumulative cultural processes. Divergent outcomes across experimental runs can be traced back to specific innovations and organizational structures. TerraLingua thus provides a platform for characterizing the mechanisms of cumulative culture and social organization in artificial populations, and can serve as a foundation for guiding real-world agentic populations to socially beneficial outcomes.

Nikita Soni, Dhruv Vijay Kunjadiya, Pratham Piyush Shah et al.

Language model training and inference ignore a fundamental linguistic fact -- there is a dependence between multiple sequences of text written by the same person. Prior work has shown that addressing this form of \textit{ecological fallacy} can greatly improve the performance of multiple smaller (~124M) GPT-based models. In this work, we ask if addressing the ecological fallacy by modeling the author's language context with a specific LM task (called HuLM) can provide similar benefits for a larger-scale model, an 8B Llama model. To this end, we explore variants that process an author's language in the context of their other temporally ordered texts. We study the effect of pre-training with this author context using the HuLM objective, as well as using it during fine-tuning with author context (\textit{HuFT:Human-aware Fine-Tuning}). Empirical comparisons show that addressing the ecological fallacy during fine-tuning alone using QLoRA improves the performance of the larger 8B model over standard fine-tuning. Additionally, QLoRA-based continued HuLM pre-training results in a human-aware model generalizable for improved performance over eight downstream tasks with linear task classifier training alone. These results indicate the utility and importance of modeling language in the context of its original generators, the authors.

Mridankan Mandal

Human Activity Recognition (HAR) on resource constrained wearables requires models that balance accuracy against strict memory and computational budgets. State of the art lightweight architectures such as TinierHAR (34K parameters) and TinyHAR (55K parameters) achieve strong accuracy, but exceed memory budgets of microcontrollers with limited SRAM once operating system overhead is considered. We present MicroBi-ConvLSTM, an ultra-lightweight convolutional-recurrent architecture achieving 11.4K parameters on average through two stage convolutional feature extraction with 4x temporal pooling and a single bidirectional LSTM layer. This represents 2.9x parameter reduction versus TinierHAR and 11.9x versus DeepConvLSTM while preserving linear O(N) complexity. Evaluation across eight diverse HAR benchmarks shows that MicroBi-ConvLSTM maintains competitive performance within the ultra-lightweight regime: 93.41% macro F1 on UCI-HAR, 94.46% on SKODA assembly gestures, and 88.98% on Daphnet gait freeze detection. Systematic ablation reveals task dependent component contributions where bidirectionality benefits episodic event detection, but provides marginal gains on periodic locomotion. INT8 post training quantization incurs only 0.21% average F1-score degradation, yielding a 23.0 KB average deployment footprint suitable for memory constrained edge devices.

Luke Meyers, Anirudh Potlapally, Yuyan Chen et al.

Plant phenology, the study of cyclical events such as leafing out, flowering, or fruiting, has wide ecological impacts but is broadly understudied, especially in the tropics. Image analysis has greatly enhanced remote phenological monitoring, yet capturing phenology at the individual level remains challenging. In this project, we deployed low-cost, animal-triggered camera traps at the Pu'u Maka'ala Natural Area Reserve in Hawaii to simultaneously document shifts in plant phenology and flora-faunal interactions. Using a combination of foundation vision models and traditional computer vision methods, we measure phenological trends from images comparable to on-the-ground observations without relying on supervised learning techniques. These temporally fine-grained phenology measurements from camera-trap images uncover trends that coarser traditional sampling fails to detect. When combined with detailed visitation data detected from images, these trends can begin to elucidate drivers of both plant phenology and animal ecology.

Antonia Weiss, Alan Xavier Elena, Uli Klümper et al.

Abstract Background Antibiotic resistance genes (ARGs) are proliferating in wastewater microbiomes, yet the biotic forces shaping their diversity remain poorly understood. Here, we integrate 14 months of metagenomic and metatranscriptomic data from a wastewater treatment plant to reveal that viruses and microeukaryotes, long-overlooked trophic actors, may play an important role in shaping bacterial and ARG diversity. Results We show that viral and microeukaryotic communities exhibit strong seasonal dynamics that cascade through the microbial food web, significantly structuring prokaryotic communities and subsequently ARG profiles. Crucially, we find that viral and microeukaryotic diversity are positively associated with bacterial diversity, which in turn shapes ARG diversity, underscoring the regulatory potential of ecological interactions. Conclusions Our findings challenge the abiotic-centric paradigm and establish the central role of multi-trophic interactions in shaping ARG dynamics in wastewater ecosystems. Video Abstract

Ilksen Topcu, Julio S. Bernal, Sanjay Antony-Babu

BackgroundWhether domestication, post-domestication spread, and breeding affected the maize leaf endosphere microbiota is poorly understood despite the well-known effects of those processes on the crop’s genetics and responses to the environment. We examined the leaf endosphere microbial communities associated with three plant groups (Zea mays): teosintes, maize landraces, and maize elite inbreds. The teosintes group included Balsas (Z. mays parviglumis) and perennial (Zea diploperennis) teosinte, and each maize (Z. mays mays) group included genotypes from Mexico and USA. We used 16S-V4 region amplicon sequencing of the leaf endophytic microbiota to infer how the microbial communities of inbred maize may have been shaped by the crop’s evolution, and whether they were affected by: (i) the transition from a perennial life history to an annual life history in the teosintes; (ii) domestication of maize from Balsas teosinte; (iii) northward spread of landrace maize from Mexico to the US; and (iii) breeding of landrace maizes to produce elite inbreds.ResultsThe leaf endophytic microbial community differed among the plant groups and genotypes, and was affected by domestication, as indicated by a decline in bacterial diversity and changes in microbial community structure between wild (teosinte) and domesticated (maize) Zea. While the microbial community structure was stringent and regulated in the teosintes, it was variable in the maize landraces and inbreds, as evidenced by greater distances to centroid based on Euclidean dissimilarity metric. This pattern was suggestive of microbial dysbiosis in the leaf endosphere associated with domestication and is consistent with predictions of the Anna Karenina principle. This finding marks the first evidence of dysbiosis associated with domestication. FAPROTAX predictions suggested that the teosintes may harbor microbial communities enriched in taxa associated with cellulolytic, chitinolytic, and nitrate respiration functions, while the maizes showed higher fermentation and nitrate reduction functions.ConclusionsOur results showed that the leaf endosphere microbial community structures in maize are consistent with alterations associated with dysbiosis. Our findings enhanced our understanding of the effects of anthropogenic processes including crop domestication, spread, and breeding on the leaf endosphere of elite maize cultivars, and may guide the development of evolutionarily-and ecologically sustainable biofertilizers and biocontrol agents.

Jan Hajič, Fabian Moss

A major locus of musicological activity-increasingly in the digital domain-is the cataloguing of sources, which requires large-scale and long-lasting research collaborations. Yet, the databases aiming at covering and representing musical repertoires are never quite complete, and scholars must contend with the question: how much are we still missing? This question structurally resembles the 'unseen species' problem in ecology, where the true number of species must be estimated from limited observations. In this case study, we apply for the first time the common Chao1 estimator to music, specifically to Gregorian chant. We find that, overall, upper bounds for repertoire coverage of the major chant genres range between 50 and 80 %. As expected, we find that Mass Propers are covered better than the Divine Office, though not overwhelmingly so. However, the accumulation curve suggests that those bounds are not tight: a stable ~5% of chants in sources indexed between 1993 and 2020 was new, so diminishing returns in terms of repertoire diversity are not yet to be expected. Our study demonstrates that these questions can be addressed empirically to inform musicological data-gathering, showing the potential of unseen species models in musicology.

Vincent A. Viblanc, Elise Huchard, Gilles Pinay et al.

Planet Earth and the biodiversity it supports are in crisis. Human impact on terrestrial, marine and freshwater ecosystems and the hundreds of thousands of organisms that inhabit them is global. To what extent can we push ecosystems before they collapse? Will species adapt to these changes and at what rate? What are the consequences, for the environment and humankind? These are some of the most pressing issues to date. Clear answers can only be addressed through long-term research programs that are extremely complex in their deployment, and by the analyses of the unique data they produce on species and ecosystem responses to change. Yet, too little institutional support and consideration have been given to long-term ecological and evolutionary research. We describe the action recently taken by the French National Center for Scientific Research (CNRS) to recognize and support long-term ecological and evolutionary research. We provide some salient examples of critical knowledge attainable only through long-term studies in ecology and evolution, before highlighting how global institutional schemes can not only support long-term research, but lead to informed conservation efforts and societal change. Now more than ever, as populism grows and fuels mis-and dis-informed politics, governmental programs are urgently needed to support data collection, establish data-grounded facts, inform political spheres, and refuel trust with society at large.

Bo Chu, Shishuai Ge, Wei He et al.

Abstract Background The insect gut microbiota forms a complex, multifunctional system that significantly affects phenotypic traits linked to environmental adaptation. Strong reproductive potential underpins the migratory success, population growth and destructive impact of the fall armyworm, Spodoptera frugiperda (J.E. Smith). However, the precise role of gut bacteria in S. frugiperda reproductive processes, distribution and transmission dynamics remains unclear. Results We examined the gut microbiota of S. frugiperda a major invasive agricultural pest, identifying Enterococcus, Enterobacter, and Klebsiella as core microorganisms present throughout its life cycle. These microbes showed heightened activity during the egg stage, early larval stages and pre-oviposition period in females. Using an axenic insect re-infection system, Enterococcus quebecensis FAW181, Klebsiella michiganensis FAW071 and Enterobacter hormaechei FAW049 were found to significantly enhance host fecundity, increasing egg production by 62.73%, 59.95%, and 56.71%, respectively. Metagenomic and haemolymph metabolomic analyses revealed a positive correlation between gut symbiotic bacteria and hormone metabolism in female S. frugiperda. Further analysis of metabolites in the insect hormone biosynthesis pathway, along with exogenous injection of juvenile hormone III and 20-hydroxyecdysone, revealed that gut microbes regulate these hormones, maintaining levels equivalent to those in control insects. This regulation supports improved fecundity in S. frugiperda, aiding rapid colonization and population expansion. Conclusions These findings emphasize the pivotal role of gut bacteria E. quebecensis FAW181, E. hormaechei FAW049, and K. michiganensis FAW071 in enhancing S. frugiperda reproduction by modulating JH III levels through JHAMT regulation and concurrently modulating the levels of 20E and its precursors via PHM. Our results provide novel insights into microbe–host symbiosis and pest management strategies for alien invasive species. Video Abstract