Biology subjects

Dasari, M.

Publications and source records attributed to Dasari, M..

3 recordsLinked to original sources

bioRxiv2022

Universal gut microbial relationships in the gut microbiome of wild baboons

Ecological relationships between bacteria mediate the services that gut microbiomes provide to their hosts. Knowing the overall direction and strength of these relationships within hosts, and their generalizability across hosts, is essential to learn how microbial ecology scales up to affect microbiome assembly, dynamics, and host health. Here we gain insight into these patterns by inferring thousands of correlations in bacterial abundance between pairs of gut microbiome taxa from extensive time series data (5,534 microbiome profiles from 56 wild baboon hosts over a 13-year period). We model these time series using a statistically robust, multinomial logistic-normal modeling framework and test the degree to which bacterial abundance correlations are consistent across hosts (i.e., "universal") or individualized to each host. We also compare these patterns to two publicly available human data sets. We find that baboon gut microbial relationships are largely universal: correlation patterns within each baboon host reflect a mixture of idiosyncratic and shared patterns, but the shared pattern dominates by almost 2-fold. Surprisingly, the strongest and most consistently correlated bacterial pairs across hosts were overwhelmingly positively correlated and typically belonged to the same family--a 3-fold enrichment compared to pairs drawn from the data set as a whole. The bias towards universal, positive bacterial correlations was also apparent in monthly samples from human infants, and bacterial families that had universal relationships in baboons also tended to be universal in human infants. Together, our results advance our understanding of the relationships that shape gut microbial ecosystems, with implications for microbiome personalization, community assembly and stability, and the feasibility of microbiome interventions to improve host health.

ecology↗

bioRxiv2020

Comparing proportional and ordinal dominance ranks reveals multiple competitive landscapes in an animal society

Across group-living animals, linear dominance hierarchies lead to disparities in access to resources, health outcomes, and reproductive performance. Studies of how dominance rank affects these outcomes typically employ one of several dominance rank metrics without examining the assumptions each metric makes about its underlying competitive processes. Here we compare the ability of two dominance rank metrics--ordinal rank and proportional or standardized rank--to predict 20 distinct traits in a well-studied wild baboon population in Amboseli, Kenya. We propose that ordinal rank best predicts outcomes when competition is density-dependent, while proportional rank best predicts outcomes when competition is density-independent. We found that for 75% (15/20) of the traits, one of the two rank metrics performed better than the other. Strikingly, all male traits were better predicted by ordinal than by proportional rank, while female traits were evenly split between being better predicted by proportional or ordinal rank. Hence, male and female traits are shaped by different competitive regimes: males competitive environments are largely driven by density-dependent resource access (e.g., access to estrus females), while females competitive environments are shaped by both density-independent resource access (e.g. distributed food resources) and density-dependent resource access. However, traits related to competition for social and mating partners are an exception to this sex-biased pattern: these traits were better predicted by ordinal rank than by proportional rank for both sexes. We argue that this method of comparing how different rank metrics predict traits of interest can be used as a way to distinguish between different competitive processes operating in animal societies.

animal behavior and cognition↗

bioRxiv2019

Differential gene expression and the importance of regulatory ncRNAs in acidophilic microorganisms

Gene expression profiles provide insight into how microorganisms respond to changing environmental conditions. However, few studies have integrated expression profile analyses of both coding genes and non-coding RNAs (ncRNAs) to characterize the functional activity of microbial community members. Here, we defined gene expression profiles from environmental and laboratory-grown acidophilic biofilms using RNASeq. In total, 15.8 million Illumina reads were mapped to the genomes of 26 acidophilic microorganisms and nine viruses reconstructed from the Richmond Mine at Iron Mountain, California. More than 99% of the genome was transcribed in three Leptospirillum species, and > 80% in the archaea G-plasma and Ferroplasma Type II. High gene expression by G-plasma and the Leptospirillum Group II UBA strain correlated with extremely acidic conditions, whereas high transcriptional expression of Leptospirillum Group III and Leptospirillum Group II 5way-CG strain occurred under higher pH and lower temperature. While expression of CRISPR Cas genes occurs on the sense strand, expression of the CRISPR loci occurs on the antisense strand in the Leptospirilli. A novel riboswitch associated with the biosynthetic pathway for the osmolyte ectoine was upregulated when each specific Leptospirillum Group II strain was growing under the conditions most favorable for it. Newly described ncRNAs associated with CO dehydrogenase (CODH) suggest regulation of expression of CODH as a CO sensor in mature biofilms in the Leptospirilli. Results reveal the ways in which environmental conditions shape transcriptional profiles of organisms growing in acidophilic microbial communities and highlight the significance of ncRNAs in regulating gene expression. IMPORTANCEMicroorganisms play important roles in environmental acidification and in metal-recovery based bioleaching processes. Therefore, characterizing how actively growing microbial communities respond to different environments is key to understanding their role in those processes. Microorganisms express their genes, both coding and non-coding, differently depending on environmental factors, thus evaluating community expression profiles inform about the ecology of actively growing microorganisms. Here we used community transcriptomic analyses to characterize gene expression profiles from biofilm communities growing under extremely acidic conditions. Results expand our knowledge of how acidophilic microorganisms respond to changes in their environment and provide insight into possible gene regulation mechanisms.

microbiology↗