Biology subjects

Kalan, L. R.

Publications and source records attributed to Kalan, L. R..

5 recordsLinked to original sources

bioRxiv2025

Complex multicellularity linked with expanded chemical arsenals in microbes

Single-celled microorganisms evolving to form cooperative multicellular units represents a key innovation in the history of life. Multicellularity is required for cell differentiation and, as such, is critical to the emergence of biological complexity. Here, we propose and find support for our hypothesis that multicellularity facilitated massive expansions in the biosynthetic potential to produce specialized metabolites across microbial life. Our systematic characterization of biosynthetic gene clusters (BGCs) across bacteria confirms that most taxa have limited predicted potential to produce natural products. In contrast with primarily unicellular lineages, we show that the origins of biosynthetic expansion in Actinomycetota, Cyanobacteriota, and Myxococcota coincide with independent origins of multicellular structures such as mycelia, filaments, and fruiting bodies. Further, we reveal that the two primary origins of expansions in specialized metabolism for fungi, corresponding to the Pezizomycotina and Agaricomycetes, similarly coincide with the emergence of complex multicellularity and fruiting body formation as well as mechanisms for self-identification during haplontic life cycles. Interestingly, all five of the biosynthetically talented multicellular microbial lineages are concomitantly enriched in carbohydrate utilization enzymes, suggesting that ancient chemical innovations have been further shaped by catabolic processes. Intraspecific cooperation shaping the evolution of specialized metabolism further informs our understanding of the major transitions in life and will help guide efforts to discover new antimicrobial compounds to counter the emergence of antibiotic resistance.

evolutionary biology↗

bioRxiv2024

Upper respiratory microbial communities of healthy populations are shaped by niche and age

BackgroundAlterations in upper respiratory microbiomes have been implicated in shaping host health trajectories, including by limiting mucosal pathogen colonization. However, limited comparative studies of respiratory microbiome development and functioning across age groups have been performed. Herein, we perform shotgun metagenomic sequencing paired with pathogen inhibition assays to elucidate differences in nasal and oral microbiome composition and functioning across healthy 24-month-old infant (n=229) and adult (n=100) populations. ResultsWe find that beta diversity of nasal and oral microbiomes varies with age, with nasal microbiomes showing greater population-level variation compared to oral microbiomes. Infant microbiome alpha diversity was significantly lower across nasal samples and higher in oral samples, relative to adults. Accordingly, we demonstrate significant differences in genus- and species-level composition of microbiomes between sites and age groups. Antimicrobial resistome patterns likewise varied across body sites, with oral microbiomes showing higher resistance gene abundance compared to nasal microbiomes. Biosynthetic gene clusters encoding specialized metabolite production were found in higher abundance across infant oral microbiomes, relative to adults. Investigation of pathogen inhibition revealed greater inhibition of gram-negative and gram-positive bacteria by oral commensals, while nasal isolates had higher antifungal activity. ConclusionsIn summary, we identify significant differences in the microbial communities inhabiting nasal and oral cavities of healthy infants relative to adults. These findings inform our understanding of the interactions impacting respiratory microbiome composition and functioning, with important implications for host health across the lifespan.

microbiology↗

bioRxiv2024

The Porcine Skin Microbiome Exhibits Broad Fungal Antagonism

The skin and its microbiome function to protect the host from pathogen colonization and environmental stressors. In this study, using the Wisconsin Miniature Swine model, we characterize the porcine skin fungal and bacterial microbiomes, identify bacterial isolates displaying antifungal activity, and use whole-genome sequencing to identify biosynthetic gene clusters encoding for secondary metabolites that may be responsible for the antagonistic effects on fungi. Through this comprehensive approach of paired microbiome sequencing with culturomics, we report the discovery of novel species of Corynebacterium and Rothia. Further, this study represents the first comprehensive evaluation of the porcine skin mycobiome and the evaluation of bacterial-fungal interactions on this surface. Several diverse bacterial isolates exhibit potent antifungal properties against fungal pathogens in vitro. Genomic analysis of inhibitory species revealed a diverse repertoire of uncharacterized biosynthetic gene clusters suggesting a reservoir of novel chemical and biological diversity. Collectively, the porcine skin microbiome represents a potential unique source of novel antifungals. HighlightsO_LIPorcine skin bacterial communities are consistent with previous reports on porcine and human skin. C_LIO_LIFungal community composition resembles mycobiomes from other mammalian skin, but not human skin. C_LIO_LIBacteria isolated from porcine skin have antimicrobial and particularly strong antifungal activity in vitro. C_LIO_LIDiscovered three new Corynebacterium species and one new Rothia species. C_LI

microbiology↗

bioRxiv2023

skDER: microbial genome dereplication approaches for comparative and metagenomic applications

An abundance of microbial genomes have been sequenced in the past two decades. For fundamental comparative genomic investigations, where the goal is to determine the major gain and loss events shaping the pangenome of a species, it is often unnecessary and computationally onerous to include all available genomes in studies. In addition, over-representation of specific lineages due to sampling and sequencing bias can have undesired effects on evolutionary analyses. To assist users with genomic dereplication, selecting a subset of representative genomes, for downstream comparative genomic investigations, we developed skDER & CiDDER (https://github.com/raufs/skDER). skDER combines recent advances to efficiently estimate average nucleotide identity (ANI) between thousands of microbial genomes with two efficient algorithms for genomic dereplication. Further, CiDDER implements an approach whereby protein clusters are determined across all genomes and genomes are iteratively selected as representatives until a user-defined saturation of the total protein space is achieved. To support ease of use, several auxiliary functionalities are implemented within the two programs, including arguments to: (i) test the number of representative genomes resulting from a variety of clustering parameters, (ii) automate downloading of genomes belonging to a bacterial species or genus by name, (iii) cluster non-representative genomes to their closest representative genomes, and (iv) automatically filter predicted plasmids and phages prior to dereplication. We further assess the effects of filtering mobile genetic elements (MGEs) on ANI and alignment fraction (AF) estimates between pairs of genomes and find that MGEs tend to slightly deflate both metrics in one species. DATA SUMMARYskDER and CiDDER are provided as open-source software implemented in Python and C++ on Github: https://github.com/raufs/skDER; with version updates tracked on Zenodo: https://zenodo.org/records/138877101. Installation of the software is supported via both Bioconda2 and Docker. Additional code and data for analyses presented in this manuscript can be found on Zenodo at: https://zenodo.org/records/138918003. Pre-computed representative genomes selected by skDER (v1.0.7) for 18 common bacterial taxonomic groups, referencing classifications from GTDB release 2144, are also provided on Zenodo at: https://zenodo.org/records/100412035. IMPACT STATEMENTDue to the increased availability of genomes for certain microbial species, performing fundamental comparative genomic investigations has become restricted to those with access to more advanced computational infrastructure. Genomic dereplication, the process of selecting distinct representative genomes to capture the breadth of a taxonomic group, thus presents a valuable solution to overcome this embarrassment of riches. Specifically, genomic dereplication allows simplifying the scale of comparative investigations while minimizing the risk of biasing analyses to specific lineages, which might be overrepresented in genomic databases. We present here two programs for genomic dereplication, one based on ANI-inference, skDER, and the other based on assessing the saturation of total coding-genes sampled, CIDDER. These tools are implemented with a variety of auxiliary options and designed for ease of use.

bioinformatics↗

bioRxiv2020

Priority effects dictate community structure and alter virulence of fungal-bacterial biofilms

A hallmark of chronic infections are polymicrobial biofilms. The forces governing assembly and maturation of these microbial ecosystems are largely unexplored but the consequences on host response and clinical outcome can be significant. In the context of wound healing, formation of a biofilm and a stable microbial community structure is associated with impaired tissue repair resulting in a non-healing chronic wound. These types of wounds can persist for years simmering below the threshold of classical clinical infection or cycling through phases of recurrent infection. In the most severe outcome amputation of lower extremities may occur if spreading infection ensues. Here we take an ecological perspective to study priority effects and competitive exclusion on overall biofilm community structure in a three-membered community of microbes derived from a chronic wound. We find that priority effects occur across both biotic and abiotic substrates, and ecological interactions can alter both fungal physiology and host inflammatory response. We show that bacterial-competition occurs for binding to fungal structures, and some species trigger the yeast-hyphae switch, resulting in enhanced neutrophil killing and inflammation. Collectively, the results presented here facilitate our understanding of fungal-bacterial microbial community dynamics and their effects on, host-microbe interactions, pathogenesis, and ultimately, wound healing.

microbiology↗