Biology subjects

Chiniquy, D.

Publications and source records attributed to Chiniquy, D..

4 recordsLinked to original sources

bioRxiv2026

Metagenome-guided substrate selection enriches Terriglobus, reveals co-occurring taxa, and enables isolation of a novel species

Microbes that remain uncultivated occupy nearly every ecosystem on the planet; this is particularly true in soils, where despite their prevalence, the roles of rarely cultivated microbes in driving biogeochemical cycles and ecosystem function remain poorly explored. We combine metagenome-informed substrate selection with enrichment sub-communities to generate reduced-complexity communities that preserve co-occurrence and expand experimental access to underrepresented soil lineages without requiring prior isolation of each member. Carbohydrate-active enzyme (CAZyme) profiles from soil-derived genomes were used to select carbon compounds predicted to enrich difficult to culture taxa, including members of the phylum Acidobacteriota. Based on 16S rRNA amplicon sequencing, we reproducibly enriched Terriglobus (Acidobacteriota) on multiple metagenome-guided substrates. Select communities with consistent presence and varying abundance of Terriglobus were passaged in a longitudinal design to generate 89 metagenomes; genus-level profiling revealed that community composition varied between biological replicates but remained consistent within replicates over time, providing diverse Acidobacteriota-containing configurations for downstream analysis. Association network inference identified a core set of co-occurring taxa that positively tracked with Terriglobus across the longitudinal series. In parallel, the substrate-guided approach led to isolation of a novel Terriglobus species, the first cultured representative of its GTDB species cluster. Together, these results establish a generalizable strategy for generating communities enriched with rarely cultivated taxa, yielding tractable systems for studying microbial interactions and community assembly in soil.

microbiology↗

bioRxiv2025

Phage-based microbiome manipulation elucidates interactions within community context

Testing microbial interaction hypotheses remains a major challenge in microbiome research. Bacteriophages have the potential to probe organism-organism interactions within complex microbiomes, yet are rarely used for this purpose. Here, we isolated nine narrow host range phages that replicate in several ecologically important Variovorax species. As Variovorax CL14 degrades the plant root-stunting hormone auxin, we used phages to eliminate V. CL14 from a rhizosphere consortium and reestablished the stunted root phenotype. We used three of the phages to deplete another Variovorax, SCN45, from complex communities to test correlation network-based hypotheses of thiamine interdependencies. Genome-resolved metagenomics revealed that specific taxa decreased in relative abundance following Variovorax depletion and could be rescued by thiamine supplementation. Thus, we confirmed thiamine production as the mechanistic basis for interdependence. These experiments lay the foundation for research that employs wildtype and engineered phages to test interaction hypotheses and for targeted microbiome manipulation.

microbiology↗

bioRxiv2025

Methane-fed microbial communities enriched from field-grown rice support diverse heterotrophic bacteria

Rice paddies naturally host aerobic methanotrophic bacteria, due to the production of methane in flooded soils. However, relatively little is known about how the activity of methanotrophs impacts the structure of the broader microbial community in this globally important agricultural environment. To address this question, we passaged 51 aerobic microbial enrichment cultures from rice rhizosphere, root, and stem samples in a chemically-defined medium with methane as the primary carbon source and electron donor. We profiled the cultures over time by 16S rRNA gene amplicon sequencing and sequenced the genomes of 40 isolates from the enrichments to gain functional insights. Taxa whose relative abundance increased during community growth on methane represented more than a dozen families, many of which are not known to utilize methane or other one-carbon substrates. Despite the selective pressure imposed by the culture condition, the final community structures were taxonomically varied rather than converging to a common composition. Genomic analysis of the sequenced isolates revealed considerable variation in likely carbon source utilization repertoires, as well as the capacity for nitrogen fixation or denitrification. Taken together, these findings support the view that methanotrophy represents a key link in the microbial food web of rice fields, with the potential for downstream effects on the abundance and activity of a wide range of community members. ImportanceRice paddies produce the primary staple food for more than half of the worlds population, but are also a major source of methane emissions. Methane-oxidizing bacteria known as methanotrophs naturally occur in rice paddies, where they consume methane that would otherwise escape to the atmosphere. Enhancing the activity of native methanotrophs could improve the sustainability of rice cultivation. However, large gaps remain in our knowledge of how increased methanotrophic activity could impact other members of rice paddy microbial communities, leaving open the possibility of unintended effects on other important microbial ecosystem functions, such as nitrogen cycling. This study sheds light on the taxonomic range and metabolic capacities of rice-associated bacteria that can benefit from the activity of native methanotrophs, laying the foundation for a broader understanding of how methanotrophs impact microbiome assembly and nutrient cycling in rice paddies.

microbiology↗

bioRxiv2020

Feature selection and causal analysis for microbiome studies in the presence of confounding using standardization

BackgroundMicrobiome studies have uncovered associations between microbes and human, animal, and plant health outcomes. This has led to an interest in developing microbial interventions for treatment of disease and optimization of crop yields which requires identification of microbiome features that impact the outcome in the population of interest. That task is challenging because of the high dimensionality of microbiome data and the confounding that results from the complex and dynamic interactions among host, environment, and microbiome. In the presence of such confounding, variable selection and estimation procedures may have unsatisfactory performance in identifying microbial features with an effect on the outcome. ResultsIn this manuscript, we aim to estimate population-level effects of individual microbiome features while controlling for confounding by a categorical variable. Due to the high dimensionality and confounding-induced correlation between features, we propose feature screening, selection, and estimation conditional on each stratum of the confounder followed by a standardization approach to estimation of population-level effects of individual features. Comprehensive simulation studies demonstrate the advantages of our approach in recovering relevant features. Utilizing a potential-outcomes framework, we outline assumptions required to ascribe causal, rather than associational, interpretations to the identified microbiome effects. We conducted an agricultural study of the rhizosphere microbiome of sorghum in which nitrogen fertilizer application is a confounding variable. In this study, the proposed approach identified microbial taxa that are consistent with biological understanding of potential plant-microbe interactions. ConclusionsStandardization enables more accurate identification of individual microbiome features with an effect on the outcome of interest compared to other variable selection and estimation procedures when there is confounding by a categorical variable.

microbiology↗