Biology subjects

Muscarella, M. E.

Publications and source records attributed to Muscarella, M. E..

4 recordsLinked to original sources

bioRxiv2018

Trait-based approach to bacterial growth efficiency

AO_SCPLOWBSTRACTC_SCPLOWBacterial growth efficiency (BGE) is the proportion of assimilated carbon that is converted into biomass and reflects the balance between growth and energetic demands. Often measured as an aggregate property of the community, BGE is highly variable within and across ecosystems. To understand this variation, we first identified how species identity and resource type affect BGE using 20 bacterial isolates belonging to the phylum Proteobacteria that were enriched from north temperate lakes. Using a trait-based approach that incorporated genomic and phenotypic information, we characterized the metabolism of each isolate and tested for predicted trade-offs between growth rate and efficiency. A substantial amount of variation in BGE could be explained at both broad (i.e., order, 20 %) and fine (i.e., strain, 58 %) taxonomic levels. While resource type was a relatively weak predictor across species, it explained > 60 % of the variation in BGE within a given species. Furthermore, a metabolic trade-off (between maximum growth rate and efficiency) and genomic features revealed that BGE is a predictable metabolic feature. Our study suggests that genomic and phylogenetic information may help predict aggregate microbial community functions like BGE and the fate of carbon in ecosystems. OO_SCPLOWRIGINALITYC_SCPLOWO_SCPCAP C_SCPCAPO_SCPLOWANDC_SCPLOW SO_SCPLOWIGNIFICANCEC_SCPLOWBacterial growth efficiency (BGE) is an important yet notoriously variable measure of metabolism that has proven difficult to predict. To better understand how assimilated carbon is allocated, we explored growth efficiency across a collection of bacteria strains using a trait-based approach. Specifically, we measured respiration and biomass formation rates for populations grown in minimal media containing one of three carbon resources. In addition, we collected a suite of physiological traits to describe each strain, and we sequenced the genome of each organism. Our results suggest that species identity and resource type may contribute to growth efficiency when measured as an aggregate property of a natural community. In addition, we identified genomic pathways that are associated with elevated BGE. The findings have implications for integrating microbial metabolism from the cellular to ecosystem scale.

microbiology↗

bioRxiv2018

Resource diversity structures aquatic bacterial communities

Microbial diversity is strongly affected by the bottom-up effects of resource availability. However, because resource pools often exist as heterogeneous mixtures of distinct molecules, resource heterogeneity may also affect community diversity. To test this hypothesis, we surveyed bacterial communities in lakes that varied in resource concentration. In addition, we characterized resource heterogeneity in these lakes using an ecosystem metabolomics approach. Overall, resource concentration and resource heterogeneity affected bacterial resource-diversity relationships. We found strong relationships between bacterial alpha-diversity (richness and evenness) and resource concentration and richness, but richness and evenness responded in different ways. Likewise, we found associations between the composition of the bacterial community and both resource concentration and composition, but the relationship with resource composition was stronger. Last, in the surveyed communities the presence of resource generalists may have reduced the effect of resource heterogeneity on community composition. These results have implications for understanding the interactions between bacteria and organic matter and suggest that changes in organic matter composition may alter the structure and function of bacterial communities.

microbiology↗

bioRxiv2017

Ecological Insights from the Evolutionary History of Microbial Innovations

Bacteria and Archaea represent the base of the evolutionary tree of life and contain the vast majority of phylogenetic and functional diversity. Because these organisms and their traits directly impact ecosystems and human health, a focus on functional traits has become increasingly common in microbial ecology. These trait-based approaches have the potential to link microbial communities and their ecological function. But an open question is how, why, and in what order microorganisms acquired the traits we observe in the present day. To address this, we reconstructed the evolutionary history of microbial traits using genomic data to understand the evolution, selective advantage, and similarity of traits in extant organisms and provide insights into the composition of genomes and communities. We used the geological timeline and physiological expectations to provide independent evidence in support of this evolutionary history. Using this reconstructed evolutionary history, we explored hypotheses related to the composition of genomes. We showed that gene transition rates can be used to make predictions about the size and type of genes in a genome: generalist genomes comprise many evolutionarily labile genes while specialist genomes comprise more highly conserved functional genes. These findings suggest that generalist organisms do not build up and hoard an array of functions, but rather tend to experiment with functions related to environmental sensing, transport, and complex resource degradation. Our results provide a framework for understanding the evolutionary history of extant microorganisms, the origin and maintenanceof traits, and linking evolutionary relatedness and ecological function.

microbiology↗

bioRxiv2017

Relic DNA contributes minimally to estimates of microbial diversity

Extracellular or \"relic\" DNA is one of the largest pools of nucleic acids in the mbiosphere 1,2. Relic DNA can influence a number of important ecological and evolutionary processes, but it may also bias estimates of microbial abundance and diversity, which has implications for understanding environmental, engineered, and host-associated ecosystems. We developed models capturing the fundamental processes that regulate the size and composition of the relic DNA pools to identify scenarios leading to biased estimates of biodiversity. Our models predict that bias increases with relic DNA pool size, but only when the species abundance distributions (SAD) of relic and intact DNA are distinct from one another. We evaluated our model predictions by quantifying relic DNA and assessing its contribution to bacterial diversity using 16S rRNA gene sequences collected from different ecosystem types, including soil, sediment, water, and the mammalian gut. On average, relic DNA made up 33 % of the total bacterial DNA pool, but exceeded 80 % in some samples. Despite its abundance, relic DNA had no effect on estimates of taxonomic and phylogenetic diversity, even in ecosystems where processes such as the physical protection of relic DNA are common and predicted by our models to generate bias. Rather, our findings are consistent with the expectation that relic DNA sequences degrade in proportion to their abundance and therefore may contribute minimally to estimates of microbial diversity.

microbiology↗