Biology subjects

Sha, S.

Publications and source records attributed to Sha, S..

8 recordsLinked to original sources

bioRxiv2026

Unlocking Sensitive Data with SPHERE in the Age of AI

Sensitive human data underpin discoveries across medicine, biology and the social sciences, yet privacy regulation often prevents sharing them with collaborators or artificial intelligence (AI) systems. We introduce SPHERE, a model-free method that makes sensitive datasets directly usable by AI and shareable for open science as a synthetic twin, while the original records never leave the local environment. Across 33 datasets spanning five scientific domains, SPHERE protects individual privacy against adversarial re-identification attacks while preserving the data's statistical structure: means, variances and correlations are reproduced exactly, effect size and P value in linear statistical analysis is numerically identical, nonlinear machine-learning utility is retained, and each twin is generated in seconds on a laptop. Frontier AI agents running on the twin reach the same scientific conclusions as on the original records. Analyses of the twin reproduce genome- and proteome-wide results at UK Biobank scale and recover the findings of landmark studies across three independent cohorts and consortia. The approach also extends to deep-learning embeddings across language, vision and time-series, with minimal utility loss. We make the Stanford Alzheimer's Disease Research Center cohort openly available for the first time, as a SPHERE twin spanning nine modalities that any registered researcher can analyze without an approval process. We release SPHERE with certification of each twin's privacy and fidelity, and an AI agent that autonomously executes research tasks on sensitive data without ever accessing it. Sensitive datasets that are currently closed to research could thus become routine inputs to open science and AI to enable key discoveries.

bioinformatics↗

bioRxiv2025

Peptide-RNA photo-crosslinks with tunable RNA chain map protein-RNA interfaces

Photocrosslinking mass spectrometry (MS) can map protein-RNA interfaces in living cells, but current isolation procedures for peptide-RNA crosslinks eliminate most RNA and therefore cannot identify the crosslinked RNA sequence. We introduce pepR-MS, a method that enriches peptide-RNA crosslinks with RNA chains of tunable length. To maximize proteomic depth, we applied pepR-MS to generate highly truncated RNA adducts, identifying over 34,000 unique crosslinks in 589 proteins of breast cancer cells and pinpointing RNA contacts in hundreds of structured domains and intrinsically disordered regions. By modulating nuclease digestion, longer RNA chains of up to five nucleotides were retained and sequenced alongside the crosslinked peptide using a specialized MS strategy. For RNA sequence assignment, we further introduce the computational tool SALT, which identified peptide-RNA sequence pairs for over 1,600 crosslinks in a single LC-MS run. Together, pepR-SALT provides a framework for mapping protein-RNA interfaces across the proteome and transcriptome at single-amino acid and nucleotide resolution.

molecular biology↗

bioRxiv2025

Characterization of the gut mycobiome in patients with non-alcoholic fatty liver disease and correlations with serum metabolome

BackgroundThe relationship between the gut mycobiome and non-alcoholic fatty liver disease (NAFLD) is largely unexplored. MethodsIn this study, we used a publicly available shotgun metagenomic sequencing dataset of fecal samples to compare the gut fungal communities of 90 NAFLD patients with those of 90 healthy controls. We examined their correlations with gut bacterial communities, host serum metabolite s, and the interactions of key taxa within these networks. ResultsOur results revealed a remarked dysbiosis in the gut mycobiome of NAFLD patients, cha racterized by a significant increase in four fungal taxa, including Pseudopithomyces sp. c174, Muc or sp. c176, Aspergillus sp. c25, and uncultured Ascochyta c213. Multi-omics analysis showed that the gut mycobiome significantly contributes to the host serum metabolome. Pseudopithomyces s p. c174 was notably associated with some beneficial blood metabolites, such as glycoursodeoxycholic acid and alpha-linolenic acid, whereas the NAFLD-enriched pro-inflammatory phenylacetic acid was linked to Aureobasidium sp. c170 and Basipetospora sp. c193. Network analysis revealed significant alterations in the gut microbiome of NAFLD patients, highlighting the potential roles of Alternaria alternata c42, Penicillium sp. c5, and uncultured Malassezia c303. Moreover, predictive models that integrated both bacterial and fungal taxa improved prediction accuracy, emphasizing the crucial role of gut fungi in NAFLD. ImportanceNon-alcoholic fatty liver disease (NAFLD) is a widespread liver condition with limited treatments. While gut bacteria have been extensively studied in NAFLD, the role of gut fungi (the mycobiome) remains poorly understood. This study fills that gap by characterizing gut fungal communities in NAFLD patients and linking these changes to their blood metabolite profiles. We found that NAFLD patients show distinct fungal imbalances, which correlate with key metabolic alterations in the host. These findings expand our understanding of NAFLD by spotlighting gut fungi as important contributors to disease progression. This insight opens new avenues for potential biomarkers and therapies targeting the gut-liver axis. ConclusionsOur findings provide a comprehensive understanding of the link between the gut mycobiome and NAFLD progression, which is essential for guiding future therapeutic research.

microbiology↗

bioRxiv2024

Top-down attention and Alzheimer's pathology impact cortical selectivity during learning,influencing episodic memory in older adults

Human aging affects the ability to remember new experiences, in part, because of altered neural function during memory formation. One potential contributor to age-related memory decline is diminished neural selectivity -- i.e., a decline in the differential response of cortical regions to preferred vs. non-preferred stimuli during event perception -- yet the factors driving variability in neural selectivity with age remain unclear. We examined the impact of top-down attention and preclinical Alzheimers disease (AD) pathology on neural selectivity during memory encoding in 156 cognitively unimpaired older participants who underwent fMRI while performing a word-face and word-scene associative memory task. Neural selectivity in face- and place-selective cortical regions was greater during events that were later remembered compared to forgotten. Critically, neural selectivity during learning positively scaled with memory-related variability in top-down attention, whereas selectivity negatively related to early AD pathology, evidenced by elevated plasma pTau181. Path analysis revealed that neural selectivity at encoding mediated the effects of age, top-down attention, and pTau181 on associative memory. Collectively, these data reveal multiple pathways that contribute to memory differences among older adults -- AD-independent reductions in top-down attention and AD-related pathology alter the precision of cortical representations of events during experience, with consequences for remembering.

neuroscience↗

bioRxiv2024

Mapping the Human Proteome with Physical Access to DNA

In a human cell, DNA is packed in histones, RNA, and chromatin-associated proteins, forming a cohesive gel. At any given moment, only a specific subset of the proteome has physical access to the DNA and organizes its structure, transcription, replication, repair and other molecular functions essential to the way the genome is read and maintained. We have developed a zero-distance photo-crosslinking approach to quantify proteins in direct contact with DNA in living cells. Collecting DNA interactomes from human breast cancer cells, we present an atlas of over one thousand proteins with physical access to DNA, and hundreds of peptide-nucleotide crosslinks pinpointing protein-DNA interfaces with single amino-acid resolution. Differential comparisons of DNA interactomes from cells undergoing treatment with estrogen or genotoxic chemotherapy recapitulated the recruitment of key transcription factors and DNA damage proteins. This opens a direct way to explore genomic regulation in a hypothesis-free manner, applicable to many organisms and systems.

molecular biology↗

bioRxiv2022

A role for brassinosteroid signaling in decision-making processes in the Arabidopsis seedling

Plants often adapt to adverse conditions via differential growth, whereby limited resources are discriminately allocated to optimize the growth of one organ at the expense of another. Little is known about the decision-making processes that underly differential growth. In this study, we developed a screen to identify decision making mutants by deploying two tools that have been used in decision theory: a well-defined yet limited budget, as well as conflict-of-interest scenarios. A forward genetic screen that combined light and water withdrawal was carried out. This identified BRASSINOSTEROID INSENSITIVE 2 (BIN2) alleles as decision mutants with "confused" phenotypes. An assessment of organ and cell length suggested that hypocotyl elongation occurred predominantly via cellular elongation. In contrast, root growth appeared to be regulated by a combination of cell division and cell elongation or exit from the meristem. Brassinosteroid signalling mutants were most severely impaired in their ability to adjust cell geometry in the hypocotyl and cell elongation as a function of distance from the quiescent centre in the root tips. This study describes a novel paradigm for root growth under limiting conditions, which depends not only on hypocotyl-versus-root trade-offs in the allocation of limited resources, but also on an ability to deploy different strategies for root growth in response to multiple stress conditions.

plant biology↗

bioRxiv2021

Weighing the DNA content of Adeno-Associated Virus vectors with zeptogram precision using nanomechanical resonators

Quantifying the composition of viral vectors used in vaccine development and gene therapy is critical for assessing their functionality. Adeno-Associated Virus (AAV) vectors, which are the most widely used viral vectors for in-vivo gene therapy, are typically characterized using PCR, ELISA, and Analytical Ultracentrifugation which require laborious protocols or hours of turnaround time. Emerging methods such as Charge-Detection Mass Spectroscopy, Static Light Scattering, and Mass Photometry offer turnaround times of minutes for measuring AAV mass, but mostly require purified AAV-based reference materials for calibration. Here, we demonstrate a method for using Suspended Nanomechanical Resonators (SNR) to directly measure both AAV mass and aggregation from a few microliters of sample within minutes. We achieve a resolution near 10 zeptograms which corresponds to 1% of the genome holding capacity of the AAV capsid. Our results show the potential of our method for providing real-time quality control of viral vectors during biomanufacturing.

bioengineering↗

bioRxiv2020

Analysis of metagenome-assembled genomes from the mouse gut microbiota reveals distinctive strain-level characteristics

The laboratorial mouse harbors a unique gut microbiota with potential value for human microbiota-associated studies. Mouse gut microbiota has been explored at the genus and species levels, but features rarely been showed at the strain level. The identification of 833,051 and 658,438 nonredundant genes of faeces and gut content samples from the laboratorial C57/BL mice showed over half of these genes were newly found compared to the previous mouse gut microbial gene catalogue. Metagenome-assembled genomes (MAGs) was used to reconstruct 46 nonredundant MAGs belonging to uncultured specieses. These MAGs included members across all phyla in mouse gut (i.e. Firmicutes, Bacteroidetes, Proteobacteria, Deferribacteres, Verrucomicrobia, and Tenericutes) and allowed a strain-level delineating of the mouse gut microbiota. Comparison of MAGs with human gut colonies revealed distinctive genomic and functional characteristics of mouses Bacteroidetes and Firmicutes strains. Genomic characteristics of rare phyla in mouse gut microbiota were demonstrated by MAG approach, including strains of Mucispirillum schaedleri, Parasutterella excrementihominis, Helicobacter typhlonius, and Akkermansia muciniphila. ImportanceThe identification of nonredundant genes suggested the existence of unknown microbes in the mouse gut samples. The metagenome-assembled genomes (MAGs) instantiated the specificity of mouse gut species and revealed an intestinal microbial correlation between mouse and human. The cultivation of faeces and gut contents sample validated the existence of MAGs and estimate their accuracy. Full-length 16S ribosomal RNA gene sequencing enabled taxonomic characterization. This study highlighted a unique ecosystem in the gut of laboratorial mice that obviously differed with the human gut flora at the strain level. The outcomes may be beneficial to researches based on laboratorial mouse models.

microbiology↗