Biology subjects

Aiken, E.

Publications and source records attributed to Aiken, E..

6 recordsLinked to original sources

bioRxiv2026

Infection and sensitization reveal stimulus-specific immune remodeling in aged skin

Aging is associated with progressive declines in skin barrier integrity and immune protection, contributing to increased susceptibility to bacterial and viral skin infections in older adults. However, how aged skin senses and responds to infection or barrier disruption remains poorly defined. Here, we characterized the age-associated cutaneous immune response to epicutaneous Staphylococcus (S.) aureus infection and ovalbumin-induced sensitization in mouse models. Bulk RNA-seq of infected tissue showed that transcriptional variation was primarily driven by infection, not age, suggesting that aged skin retains a broadly inducible response to microbial challenge. In contrast, microneedle patch (MNP) sampling of skin interstitial fluid, which provides cellular resolution, revealed age-dependent differences in local immune dynamics after S. aureus infection, including altered magnitude and kinetics of cellular recruitment, such as an attenuated cutaneous T cell response in older mice. MNP profiling further showed that ovalbumin sensitization elicited a localized immune program distinct from the S. aureus response, which was incompletely reflected in systemic measurements. Together, these data demonstrate that aging does not uniformly impair cutaneous immunity but instead is a context-dependent remodeling of local tissue immune dynamics.

microbiology↗

bioRxiv2026

Aphids capture plant inter- and intraspecific chemodiversity

The role of chemodiversity in plant-insect interactions is widely recognised. However, our understanding of the extent to which chemodiversity connects both partners remains limited. Here, we investigated how aphid chemistry is linked to their plant diet and whether aphids capture plant inter- and intraspecific chemodiversity. Up to 93% of aphid chemical features were detected in plants. Untargeted metabolomics of aphids feeding on diets composed of distinct species or chemotypes within species unveiled the aphid capacity to capture inter- and intraspecific chemodiversity. Multiple chemodiversity indices and metabolic features significantly tracked diet variation and plant chemotypes were reflected in aphid metabolites. These features included phenolics and amino acids, likely ingested with the phloem sap, and fatty acids and terpenoids, potentially captured from the leaf surface. Overall, these findings expand our knowledge of the aphid plant-derived chemical repertoire and highlight that plant chemodiversity can be transmitted, supporting the need for chemodiversity preservation programs.

ecology↗

bioRxiv2026

Species and strain diversity in Staphylococcus drive divergent host responses in human skin

The skin microbiome regulates key skin processes, yet the functional diversity of a dominant genus, Staphylococcus, remains poorly resolved at the strain level for multiple species across its pathogenic and commensal continuum. It is likely that Staphylococcus effects on skin are diverse at these finest taxonomic resolutions, but current skin models lack the physiological relevance and scalability needed to profile this diversity. Using an organotypic 3D human skin model (reconstructed human epidermis, RHE), we profiled skin responses to 187 Staphylococcus strains across seven dominant species. Canonically pathogenic species (e.g., S. aureus) induced broad inflammatory responses, whereas prototypical commensal species (e.g., S. hominis) elicited more nuanced effects on innate immune and skin barrier responses. Strikingly, S. epidermidis displayed pronounced strain-level heterogeneity, with subsets inducing either commensal or pathogen-like responses despite lacking canonical virulence factors, suggesting pleiotropic effects. Comparative genomics, dual-transcriptomics, untargeted metabolomics, and growth phenotyping revealed species- and strain-specific traits underlying these differential effects on RHE, including the presence of select cell surface proteins and differential arginine metabolism. Together, our study provides the first high-throughput, species- and strain-resolved analysis of skin-Staphylococcus interactions, offering mechanistic insights and a platform for microbiome-based strategies to modulate skin inflammation and diseases. One-line summaryHigh-throughput profiling of Staphylococcus in a human skin model shows that species- and strain-level diversity underlies a continuum of host barrier and immune responses.

microbiology↗

bioRxiv2025

Host-specific bacterial modulation of airway gene expression and alternative splicing

The human microbiome varies extensively between individuals. While there are numerous studies investigating the effects of inter-individual differences on microbiome composition, there are few studies investigating inter-individual effects on microbial modulation of the host, or host-specific effects. To address this knowledge gap, we colonized human bronchial epithelial air-liquid interface tissue cultures generated from six different adults with one of three phylogenetically diverse bacteria and compared how each microbe differentially modulated host gene expression in each of the six donors. Microbial treatment had the strongest effect on transcription, followed by donor-specific effects. Gene pathways differed markedly in their donor- and microbe-specificity; interferon expression was highly donor-dependent while transcription of epithelial barrier and antibacterial innate immunity genes were predominantly microbially driven. Moreover, we evaluated whether microbial regulation of alternative splicing was modulated by donor. Strikingly, we found significant non-redundant, donor-specific regulation of alternative splicing exclusively in the Gram-positive commensal microbes. These findings highlight that microbial effects on the human airway epithelium are not only species-specific but also deeply individualized, scoring the importance of host context in shaping microbe-induced transcriptional and splicing responses.

microbiology↗

bioRxiv2024

TEAL-seq: Targeted Expression Analysis Sequencing

Metagenome sequencing enables genetic characterization of complex microbial communities. However, determining the activity of isolates within a community presents several challenges including the wide range of organismal and gene expression abundances, the presence of host RNA, and low microbial biomass at many sites. To address these limitations, we developed "targeted expression analysis sequencing" or TEAL-seq, enabling sensitive species-specific analyses of gene expression using highly multiplexed custom probe pools. For proof-of-concept we targeted about 1,700 core and accessory genes of Staphylococcus aureus and S. epidermidis, two key species of the skin microbiome. Two targeting methods were applied to laboratory cultures and human nasal swab specimens. Both methods showed a high degree of specificity, with >90% reads on target, even in the presence of complex microbial or human background DNA/RNA. Targeting using molecular inversion probes demonstrated excellent correlation in inferred expression levels with bulk RNA-seq. Further, we show that a linear pre-amplification step to increase the amount of nucleic acids for analysis yielded consistent and predictable results when applied to complex samples and enabled profiling of expression from as little as 1 ng of total RNA. TEAL-seq is much less expensive than bulk metatranscriptomic profiling, enables detection across a greater dynamic range, and uses a strategy that is readily configurable for determining the transcriptional status of organisms in any microbial community. IMPORTANCEThe gene expression patterns of bacteria in microbial communities reflect their activity and interactions with other community members. Measuring gene expression in complex microbiome contexts is challenging, however, due to the large dynamic range of microbial abundances and transcript levels. Here we describe an approach to assessing gene expression for specific species of interest using highly multiplexed pools of targeting probes. We show that an isothermal amplification step can allow profiling of low biomass samples. TEAL-seq should be widely adaptable to the study of microbial activity in natural environments.

genomics↗

bioRxiv2024

Fast Targeted Metabolomics for Analyzing Metabolic Diversity of Bacterial Indole Derivatives in ME/CFS Gut Microbiome

Disruptions in microbial metabolite interactions due to gut microbiome dysbiosis and metabolomic shifts may contribute to Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) and other immune-related conditions. The aryl hydrocarbon receptor (AhR), activated upon binding various tryptophan metabolites, modulates host immune responses. This study investigates whether the metabolic diversity--the concentration distribution--of bacterial indole pathway metabolites can differentiate bacterial strains and classify ME/CFS samples. A fast targeted liquid chromatography-parallel reaction monitoring method at a rate of 4 minutes per sample was developed for large-scale analysis. This method revealed significant metabolic differences in indole derivatives among B. uniformis strains cultured from human isolates. Principal component analysis identified two major components (PC1, 68.9%; PC2, 18.7%), accounting for 87.6% of the variance and distinguishing two distinct B. uniformis clusters. The metabolic difference between clusters was particularly evident in the relative contributions of indole-3-acrylate and indole-3-aldehyde. We further measured concentration distributions of indole derivatives in ME/CFS by analyzing fecal samples from 10 patients and 10 healthy controls using the fast targeted metabolomics method. An AdaBoost-LOOCV model achieved moderate classification success with a mean LOOCV accuracy of 0.65 (Control: precision of 0.67, recall of 0.60, F1-score of 0.63; ME/CFS: precision of 0.64, recall of 0.7000, F1-score of 0.67). These results suggest that the metabolic diversity of indole derivatives from tryptophan degradation, facilitated by the fast targeted metabolomics and machine learning, is a potential biomarker for differentiating bacterial strains and classifying ME/CFS samples. Mass spectrometry datasets are accessible at the National Metabolomics Data Repository (ST002308, DOI: 10.21228/M8G13Q; ST003344, DOI: 10.21228/M8RJ9N; ST003346, DOI: 10.21228/M8RJ9N).

biochemistry↗