Biology subjects

Schmidt, M. L.

Publications and source records attributed to Schmidt, M. L..

12 recordsLinked to original sources

bioRxiv2026

Cyanobacterial cohorts structure the diversity, abundance, and metabolism of heterotrophic bacteria in Lake Erie

Eutrophication and warming in Lake Erie create two microbial threats: cyanobacterial harmful algal blooms (cHABs) that can produce toxins, and seasonal hypoxia driven by microbial respiration. These phenomena are often studied separately, with cHABs research focused on the Western basin and hypoxia on the Central basin. We conducted lakewide microbial sampling at three time points in 2024 (May, August, and September), integrating physicochemical data, cyanotoxin quantification, amplicon sequencing, and flow cytometry. We demonstrate that cyanobacteria form spatially and seasonally distinct "cohorts" that act as hubs structuring abundant, diverse, and active communities across all basins. These cohorts display distinct relationships with heterotrophic communities, with colonial, bloom-forming cohorts (i.e., C1: Microcystis, C2: Pseudanabaena) associated with higher richness and evenness, the picocyanobacterium C3: Cyanobium with increased heterotrophic abundance, and C2: Pseudanabaena additionally associated with increased numbers of metabolically active cells. Neither temperature nor nutrient concentrations consistently explained these patterns, although total phosphorus correlated with bloom-forming C1 and C2 cohorts. The cohorts also formed structured "consortia" with heterotrophic taxa, with each cyanobacterial group associated with consistent sets of heterotrophic partners. Together, these results are consistent with a model in which cyanobacterial abundance increases heterotrophic growth and respiration, suggesting a lakewide pathway linking cHABs to oxygen demand and hypoxia. IMPORTANCECyanobacterial harmful algal blooms and hypoxia are two microbial processes shaping water quality in Lake Erie, yet they are typically studied separately and at basin-specific scales. We link cyanobacterial abundance to heterotrophic metabolism at a lakewide scale. We show that cyanobacterial abundance is associated with heterotrophic diversity, abundance, and metabolic activity, with contrasting patterns across cyanobacterial functional groups. These relationships were not explained by temperature nor consistently by nutrients, although cyanobacterial distribution in the Central basin is likely linked to nutrient availability as a result of upwellings and basin-wide gyres. Bloom-forming and picocyanobacterial cohorts play fundamentally different roles in structuring microbial diversity and biomass, with implications for how bloom management influences ecosystem metabolism. By identifying cyanobacteria as a major predictor of microbial biomass and activity, this work reveals a spatially-explicit pathway connecting cyanobacterial primary production to oxygen demand, suggesting that managing blooms may regulate oxygen depletion.

microbiology↗

bioRxiv2025

Higher methanotroph abundance and bottom-water methane in ponds with floating photovoltaic arrays

Floating photovoltaic (FPV) arrays alter the methane (CH4) cycling dynamics of waterbodies on which they are deployed. Here, we investigated dissolved CH4 dynamics and associated CH4 cycling microbial communities (methanogens and methanotrophs) in the second year of FPV deployment (70% aerial coverage) in experimental ponds. We found that bottom-water CH4 concentrations were twice as high in ponds with FPV compared to those without, while surface water CH4 concentrations were orders of magnitude lower than bottom-waters, but did not differ between treatments. There was no change in the relative abundances of putative sediment methanogens or methanotrophs, but FPV restructured methanogen communities. FPV promoted late-summer methanotroph blooms in the water column, with abundances surpassing 1,000,000 cells mL-1. We conclude that prolonged periods of CH4 production in low oxygen FPV ponds favored blooms of methanotrophs, that may mitigate diffusive CH4 emissions to the atmosphere by consuming dissolved CH4.

ecology↗

bioRxiv2025

Interpreting UniFrac with Absolute Abundance: A Conceptual and Practical Guide

{beta}-diversity is central to microbial ecology, yet commonly used metrics overlook changes in microbial load, limiting their ability to detect ecologically meaningful shifts. Popular for incorporating phylogenetic relationships, UniFrac distances currently default to relative abundance and therefore omit important variation in microbial abundances. As quantifying absolute abundance becomes more accessible, integrating this information into {beta}-diversity analyses is essential. Here, we introduce Absolute UniFrac (UA), a variant of Weighted UniFrac that incorporates absolute abundances. Using simulations and a reanalysis of four 16S rRNA metabarcoding datasets (from a nuclear reactor cooling tank, the mouse gut, a freshwater lake, and the peanut rhizospere), we demonstrate that Absolute UniFrac captures microbial load, composition, and phylogenetic relationships. While this can improve statistical power to detect ecological shifts, we also find Absolute Unifrac can be strongly correlated to differences in cell abundances alone. To balance these effects, we also incorporate absolute abundance into the generalized extension (GUA) that has a tunable parameter to adjust the influence of abundance and composition. Finally, we benchmark GUA and show that although computationally slower than conventional alternatives, GUA is comparably insensitive to realistic noise in load estimates compared to conventional alternatives like Bray-Curtis dissimilarities, particularly at lower . By coupling phylogeny, composition, and microbial load, Absolute Unifrac integrates three dimensions of ecological change, better equipping microbial ecologists to quantitatively compare microbial communities.

microbiology↗

bioRxiv2025

Hydrodynamic Circulation, Ecological Drift, and Homogeneous Selection Shape Microbial Communities and Biogeochemical Cycling in Lake Ontario

The Laurentian Great Lakes hold 21% of the worlds surface freshwater and supply drinking water to nearly 40 million people. We provide the first evidence that wind-driven upwelling restructures microbial communities in Lake Ontario, with its effects sustained and redistributed by an internal Kelvin wave propagating along the shoreline. We combine 16S rRNA metabarcoding, absolute abundance quantification via flow cytometry, and hydrodynamic profiling to link physical processes to community composition. While thermal stratification organizes microbial communities by depth and season, this vertical structure arises from contrasting mechanisms: homogenizing selection in surface waters and dispersal limitation and drift in the hypolimnion. Kelvin wave-driven upwelling disrupts this scaffold, displacing rare taxa into the surface and creating novel coastal communities predicted to be enriched in methane oxidation and sulfur metabolism genes--functional traits absent elsewhere in the lake. We observed a Kelvin wave lasting over two weeks and propagating eastward at [~]60 km day-{superscript 1}. Given the [~]10-12 day recurrence of wind events during the stratified season, at any time at least one segment of Lake Ontarios coastline is experiencing upwelling. These recurrent upwellings, sustained and redistributed by Kelvin waves, remodel microbial communities on ecologically relevant timescales. They act as a biological disturbance overriding stratification, mobilizing rare functional potential, and assembling novel coastal microbial communities. As climate change lengthens and intensifies stratified periods and reshapes large-lake circulation, understanding how physical forcing governs microbial assembly is essential for forecasting the biogeochemical future of Earths great lakes--especially in shoreline zones where ecological shifts directly affect human communities.

ecology↗

bioRxiv2023

Antigenic cartography using variant-specific hamster sera reveals substantial antigenic variation among Omicron subvariants

SARS-CoV-2 has developed substantial antigenic variability. As the majority of the population now has pre-existing immunity due to infection or vaccination, the use of experimentally generated animal immune sera can be valuable for measuring antigenic differences between virus variants. Here, we immunized Syrian hamsters by two successive infections with one of eight SARS-CoV-2 variants. Their sera were titrated against 14 SARS-CoV-2 variants and the resulting titers visualized using antigenic cartography. The antigenic map shows a condensed cluster containing all pre-Omicron variants (D614G, Alpha, Delta, Beta, Mu, and an engineered B.1+E484K variant), and a considerably more distributed positioning among a selected panel of Omicron subvariants (BA.1, BA.2, BA.4/5, the BA.5 descendants BF.7 and BQ.1.18; the BA.2.75 descendant BN.1.3.1; and the BA.2-derived recombinant XBB.2). Some Omicron subvariants were as antigenically distinct from each other as the wildtype is from the Omicron BA.1 variant. The results highlight the potential of using variant-specifically infected hamster sera for the continued antigenic characterisation of SARS-CoV-2.

immunology↗

bioRxiv2021

Post-entry, spike-dependent replication advantage of B.1.1.7 and B.1.617.2 over B.1 SARS-CoV-2 in an ACE2-deficient human lung cell line

Epidemiological data demonstrate that SARS-CoV-2 variants of concern (VOC) B.1.1.7 and B.1.617.2 are more transmissible and infections are associated with a higher mortality than non-VOC virus infections. Phenotypic properties underlying their enhanced spread in the human population remain unknown. B.1.1.7 virus isolates displayed inferior or equivalent spread in most cell lines and primary cells compared to an ancestral B.1 SARS-CoV-2, and were outcompeted by the latter. Lower infectivity and delayed entry kinetics of B.1.1.7 viruses were accompanied by inefficient proteolytic processing of spike. B.1.1.7 viruses failed to escape from neutralizing antibodies, but slightly dampened induction of innate immunity. The bronchial cell line NCI-H1299 supported 24- and 595-fold increased growth of B.1.1.7 and B.1.617.2 viruses, respectively, in the absence of detectable ACE2 expression and in a spike-determined fashion. Superior spread in NCI-H1299 cells suggests that VOCs employ a distinct set of cellular cofactors that may be unavailable in standard cell lines.

microbiology↗

bioRxiv2021

When are bacteria really gazelles? Comparing patchy ecologies with dimensionless numbers

From micro to planetary scales, spatial heterogeneity--patchiness--is ubiquitous in ecological systems, defining the environments in which organisms move and interact. While this fact has been recognized for decades, most large-scale ecosystem models still use spatially averaged "mean fields" to represent natural populations, while fine-scale, spatially explicit models are mostly restricted to particular organisms or systems. In a conceptual paper, Grunbaum (2012, Interface Focus 2: 150-155) introduced a heuristic framework, based on three dimensionless ratios quantifying movement, reproduction, and resource consumption, to characterize patchy ecological interactions and identify when mean-field assumptions are justifiable. In this paper, we calculated Grunbaums dimensionless numbers for 33 real interactions between consumers and their resource patches in terrestrial, aquatic, and aerial environments. Consumers ranged in size from bacteria to blue whales, and patches lasted from minutes to millennia, spanning spatial scales of mm to hundreds of km. We found that none of the interactions could be accurately represented by a purely mean-field model, though 26 of them (79%) could be partially simplified by averaging out movement, reproductive, or consumption dynamics. Clustering consumer-resource pairs by their non-dimensional ratios revealed several unexpected dynamic similarities between disparate interactions. For example, bacterial Pseudoalteromonas exploit nutrient plumes in a similar manner to Mongolian gazelles grazing on ephemeral patches of steppe vegetation. Our findings suggest that dimensional analysis is a valuable tool for characterizing ecological patchiness, and can link the dynamics of widely different systems into a single quantitative framework.

ecology↗

bioRxiv2021

SARS-CoV-2 Beta variant infection elicits potent lineage-specific and cross-reactive antibodies

SARS-CoV-2 Beta variant of concern (VOC) resists neutralization by major classes of antibodies from non-VOC COVID-19 patients and vaccinated individuals. Here, serum of Beta variant infected patients revealed reduced cross-neutralization of non-VOC virus. From these patients, we isolated Beta-specific and cross-reactive receptor-binding domain (RBD) antibodies. The Beta-specificity results from recruitment of novel VOC-specific clonotypes and accommodation of VOC-defining amino acids into a major non-VOC antibody class that is normally sensitive to these mutations. The Beta-elicited cross-reactive antibodies share genetic and structural features with non-VOC-elicited antibodies, including a public VH1-58 clonotype targeting the RBD ridge independent of VOC mutations. These findings advance our understanding of the antibody response to SARS-CoV-2 shaped by antigenic drift with implications for design of next-generation vaccines and therapeutics. One sentence summarySARS-CoV-2 Beta variant elicits lineage-specific antibodies and antibodies with neutralizing breadth against wild-type virus and VOCs.

immunology↗

bioRxiv2021

Enhanced fitness of SARS-CoV-2 variant of concern B.1.1.7, but not B.1.351, in animal models

Emerging variants of concern (VOCs) drive the SARS-CoV-2 pandemic. We assessed VOC B.1.1.7, now prevalent in several countries, and VOC B.1.351, representing the greatest threat to populations with immunity to the early SARS-CoV-2 progenitors. B.1.1.7 showed a clear fitness advantage over the progenitor variant (wt-S614G) in ferrets and two mouse models, where the substitutions in the spike glycoprotein were major drivers for fitness advantage. In the "superspreader" hamster model, B.1.1.7 and wt-S614G had comparable fitness, whereas B.1.351 was outcompeted. The VOCs had similar replication kinetics as compared to wt-S614G in human airway epithelial cultures. Our study highlights the importance of using multiple models for complete fitness characterization of VOCs and demonstrates adaptation of B.1.1.7 towards increased upper respiratory tract replication and enhanced transmission in vivo. Summary sentenceB.1.1.7 VOC outcompetes progenitor SARS-CoV-2 in upper respiratory tract replication competition in vivo.

microbiology↗

bioRxiv2020

A SARS-CoV-2 neutralizing antibody protects from lung pathology in a COVID-19 hamster model

The emergence of SARS-CoV-2 led to pandemic spread of coronavirus disease 2019 (COVID-19), manifesting with respiratory symptoms and multi-organ dysfunction. Detailed characterization of virus-neutralizing antibodies and target epitopes is needed to understand COVID-19 pathophysiology and guide immunization strategies. Among 598 human monoclonal antibodies (mAbs) from ten COVID-19 patients, we identified 40 strongly neutralizing mAbs. The most potent mAb CV07-209 neutralized authentic SARS-CoV-2 with IC50 of 3.1 ng/ml. Crystal structures of two mAbs in complex with the SARS-CoV-2 receptor-binding domain at 2.55 and 2.70 [A] revealed a direct block of ACE2 attachment. Interestingly, some of the near-germline SARS-CoV-2 neutralizing mAbs reacted with mammalian self-antigens. Prophylactic and therapeutic application of CV07-209 protected hamsters from SARS-CoV-2 infection, weight loss and lung pathology. Our results show that non-self-reactive virus-neutralizing mAbs elicited during SARS-CoV-2 infection are a promising therapeutic strategy.

immunology↗

bioRxiv2018

Using machine learning to associate bacterial taxa with functional groups through flow cytometry, 16S rRNA gene sequencing, and productivity data

High-(HNA) and low-nucleic acid (LNA) bacteria are two operational groups identified by flow cytometry (FCM) in aquatic systems. HNA cell density often correlates strongly with heterotrophic production, while LNA cell density does not. However, which taxa are specifically associated with these groups, and by extension, productivity has remained elusive. Here, we addressed this knowledge gap by using a machine learning-based variable selection approach that integrated FCM and 16S rRNA gene sequencing data collected from 14 freshwater lakes spanning a broad range in physicochemical conditions. There was a strong association between bacterial heterotrophic production and HNA absolute cell abundances (R2 = 0.65), but not with the more abundant LNA cells. This solidifies findings, mainly from marine systems, that HNA and LNA could be considered separate functional groups, the former contributing a disproportionately large share of carbon cycling. Taxa selected by the models could predict HNA and LNA absolute cell abundances at all taxonomic levels, with the highest performance at the OTU level. Selected OTUs ranged from low to high relative abundance and were mostly lake system-specific (89.5%-99.2%). A subset of selected OTUs was associated with both LNA and HNA groups (12.5%-33.3%) suggesting either phenotypic plasticity or within-OTU genetic and physiological heterogeneity. These findings may lead to the identification of systems-specific putative ecological indicators for heterotrophic productivity. Generally, our approach allows for the association of OTUs with specific functional groups in diverse ecosystems in order to improve our understanding of (microbial) biodiversity-ecosystem functioning relationships. ImportanceA major goal in microbial ecology is to understand how microbial community structure influences ecosystem functioning. Research is limited by the ability to readily culture most bacteria present in the environment and the difference in bacterial physiology in situ compared to in laboratory culture. Various methods to directly associate bacterial taxa to functional groups in the environment are being developed. In this study, we applied machine learning methods to relate taxonomic data obtained from marker gene surveys to functional groups identified by flow cytometry. This allowed us to identify the taxa that are associated with heterotrophic productivity in freshwater lakes and indicated that the key contributors were highly system-specific, regularly rare members of the community, and that some could switch between being low and high contributors. Our approach provides a promising framework to identify taxa that contribute to ecosystem functioning and can be further developed to explore microbial contributions beyond heterotrophic production.

ecology↗

bioRxiv2017

Microhabitats shape diversity-productivity relationships in freshwater bacterial communities

Eukaryotic communities commonly display a positive relationship between biodiversity and ecosystem function (BEF) but the results have been mixed when assessed in bacterial communities. Habitat heterogeneity, a factor in eukaryotic BEFs, may explain these variable observations but it has not been thoroughly evaluated in bacterial communities. Here, we examined the impact of habitat on the relationship between diversity assessed based on richness, evenness, or phylogenetic diversity, and heterotrophic productivity. We sampled co-occurring free-living (more homogenous) and particle-associated (more heterogeneous) bacterial habitats in a freshwater, estuarine lake. Diversity measures, and not environmental variables, were the best predictors of particle-associated heterotrophic production. There was a strong, positive, linear relationship between particle-associated bacterial richness and heterotrophic productivity that strengthened with evenness. There were no observable BEF trends in free-living bacterial communities. Across both habitats, communities with more phylogenetically related taxa had higher per-capita heterotrophic production than communities of phylogenetically distantly related taxa. Our findings show that heterotrophic bacterial productivity is positively correlated with evenness and richness, negatively with phylogenetic diversity, and that BEF relationships are contingent on microhabitats. Our work adds to the understanding of the highly distinct contributions to community diversity and ecosystem functioning contributed by bacteria in free-living and particle-associated aquatic habitats.

ecology↗