Biology subjects

Moses, C.

Publications and source records attributed to Moses, C..

4 recordsLinked to original sources

bioRxiv2026

FiberPro 1.0: Multiagent AI-Guided Design for High-Throughput Production and Conformal Deposition of Functional Protein Micro/Nanofibers

Functional protein micro/nanofibers integrate high specific surface areas with bioactive architectures but remain hampered low production throughput and severe processing instability. Focused rotary jet spinning (FRJS) shows promising to break these throughput constraints while enabling direct, conformal deposition onto complex, irregular substrates. However, navigating FRJS's narrow processing windows in proteins remains failure-prone without closed-loop experimental guidance. Here, we report FiberPro 1.0, a large language model driven multi agent framework that unites high-throughput spinning with real-time experimental feedback for autonomous design, execution, and optimization. Across three protein systems, FiberPro 1.0 converged on spinnable formulations within an average of two iterations. To demonstrate high-throughput conformal deposition in a translational setting, FiberPro designed a zein-based active packaging system applied directly onto diverse food matrices. The resulting conformal coating combined potent antibacterial activity with real-time freshness monitoring, markedly suppressing Escherichia coli and extending shelf life. This work connects autonomous AI reasoning with high-throughput processing, establishing a verifiable route for scalable manufacturing and conformal coating of functional protein micro/nanofibers.

bioengineering↗

bioRxiv2026

Mapping tsetse fly connectivity in Uganda with machine learning landscape genetics

Introduction - Tsetse flies (genus Glossina) are biting insects that transmit human and animal trypanosomiases across sub-Saharan Africa, and sustainable vector control depends on understanding dispersal barriers and reinvasion routes. Despite major progress toward elimination, Uganda remains at risk for both human forms of the disease (Trypanosoma brucei gambiense and T. b. rhodesiense) and planners still lack reliable maps of tsetse movement and reinvasion risk. Methods and Results - We address this gap with machine-learning landscape genetics and species distribution models, integrating estimates of population genetic distance and geospatial environmental data to predict and map Glossina fuscipes fuscipes connectivity across Uganda and western Kenya. Inputs included microsatellite genotypes from 11 loci genotyped in 2,736 flies sampled from 87 localities and remotely sensed environmental predictors summarized along least-cost paths. Random forest models predicted patterns of genetic differentiation better than distance-only models, supporting the use of a machine-learning framework for connectivity inference across complex heterogeneous landscapes, and identified variables related to temperature and water availability as the strongest predictors of genetic connectivity. Conclusions - Combining landscape genetics predictions of connectivity with a species distribution model revealed regions with high habitat suitability but low connectivity that represent priority zones for area-wide integrated pest management strategies, including established riverine control tools such as tiny targets and other targeted interventions aimed at reducing reinvasion risk. These results provide biologically interpretable maps and quantitative uncertainty metrics that can guide targeted tsetse control, while providing a transferable analytical pipeline for modeling and mapping genetic connectivity across other species and landscapes.

evolutionary biology↗

bioRxiv2025

Evolutionary hotspots of structural variation drive inter-individual differences in the expression of fusion transcripts in the human brain

While most protein-coding regions in our genome are highly conserved, phenotypic variation largely arises from differences in gene transcription, splicing, and translation. Intra-gene splicing variations are a known source of inter-individual differences. However, inter-gene splicing events, which generate fusion transcripts--RNA molecules combining exons from multiple distinct genes--are less explored. Fusion transcripts are well-studied in cancer, but their expression and inter-individual variability in normal human tissues has not been thoroughly investigated. We conducted a genome-wide fusion transcript analysis in postmortem human brain tissues from 276 individuals, identifying 717 distinct fusion transcripts. Many had protein coding potential, further supported in some cases by ribosome profiling data. Fusion transcripts that were present in only part of the human population were predominantly located within segmental duplication (SD) "hotspots"; highly copy number-variable genomic regions linked to neurodevelopmental and neurodegenerative diseases. None of these variable fusion transcripts were present in chimpanzee or rhesus macaque, suggesting they are human-specific. We confirmed that SD-derived fusion transcripts arise from structural genomic rearrangements in the human population, previously associated with neurodevelopmental and neurodegenerative disease risk. Inter-individual variation in fusion transcript expression represents an overlooked source of genetic diversity, with potential to contribute to differences in disease susceptibility.

molecular biology↗

bioRxiv2022

Divergent MEK/ERK and AMPK signaling dictate lipogenic plasticity and dependence on fatty acid synthesis in Glioblastoma

Deregulated de novo lipid synthesis (DNLS) is a potential druggable vulnerability in Glioblastoma (GBM), a highly lethal and incurable cancer. Yet the molecular mechanisms that determine susceptibility to DNLS-targeted therapies remain unknown, and the lack of brain-penetrant inhibitors of DNLS has prevented their clinical evaluation as GBM therapeutics. Here, we report that YTX-7739, a clinical-stage, brain-penetrant inhibitor of stearoyl CoA desaturase (SCD), triggers lipotoxicity in patient-derived GBM stem-like cells (GSCs) and inhibits fatty acid desaturation in GSCs orthotopically implanted in mice. When administered as a single agent, or particularly in combination with the first line GBM chemotherapy, Temozolomide (TMZ), YTX-7739 showed therapeutic efficacy in orthotopic GSC mouse models owing to its lipotoxicity and its ability to impair DNA damage repair. Leveraging genetic, pharmacological, and physiological manipulation of key signaling nodes in gliomagenesis, we uncover that aberrant MEK/ERK signaling and its repression of the energy sensor AMP-activated protein kinase (AMPK) primarily drives therapeutic vulnerability to SCD and other DNLS inhibitors. Conversely, AMPK activation mitigates lipotoxicity and renders GSCs impervious to the loss of DNLS, both in culture and in vivo, by decreasing the saturation state of phospholipids and diverting toxic lipids into lipid droplets. Altogether, our findings reveal mechanisms of metabolic plasticity in GSCs and provide a framework for rational integration of DNLS-targeted therapies for the treatment of GBM.

cancer biology↗