Biology subjects

Ayala, E.

Publications and source records attributed to Ayala, E..

6 recordsLinked to original sources

bioRxiv2026

Convergent antigenic drift of the influenza hemagglutinin lateral patch across time and species

The lateral patch epitope of the H1 hemagglutinin (HA) was a dominant target of antibodies following exposure to the 2009 pandemic H1N1 virus. However, the conservation and potential for antigenic drift in the lateral patch remain unresolved. Here, we used lateral patch-specific monoclonal antibodies (mAbs) to understand the antigenicity of the lateral patch of human, avian, and swine H1Nx viruses spanning from 1918 to 2022. We identified discrete mutations that evaded lateral patch-targeting mAbs in pre- and post-2009 H1N1 viruses, leading to genetic differences in lateral patch-targeting antibodies in individuals across birth years. We observed that the lateral patch remains well conserved across zoonotic sources, suggesting existing lateral patch antibodies could protect against a future H1Nx pandemic. Together, these data support that lateral patch antigenic drift has shaped the human B cell repertoire against influenza viruses and that the lateral patch remains an attractive target for pandemic preparedness.

microbiology↗

bioRxiv2026

Structural insights into antibody responses against influenza A virus in its natural reservoir

While influenza A virus undergoes rapid antigenic drift in humans, at least some subtypes, such as H3, have relatively stable antigenicity in natural waterfowl reservoirs, despite the presence of immune pressure. However, the underlying mechanisms remain poorly understood. This study identified and characterized 187 antibodies to H3 hemagglutinin from experimentally infected mallard ducks, 18 of which were further analyzed by cryo-EM. Compared with human H3 antibodies, duck H3 antibodies exhibited higher glycan-binding propensity, more balanced immunodominance hierarchy, and targeted distinct epitopes. Other unique features of duck H3 antibodies included a convergent CDR H3-independent heavy chain-only binding mode and an N-glycosylated CDR H3 as decoy receptor. By annotating duck immunoglobulin germline genes, we also demonstrated the importance of gene conversion in duck H3 antibodies. Overall, our findings provide insights into how millennia of coevolution have shaped the interplay between influenza A virus antigenic drift and antibody responses in the natural reservoir.

immunology↗

bioRxiv2025

Cyclin Y Overexpression Drives a Fatal Metabolic Syndrome via Defective Glucose Homeostasis

Cyclin Y (CCNY) is a membrane-associated, non-canonical cyclin best known for regulating WNT/beta-catenin signaling via the recruitment of CDK14/16 protein kinases. Whereas its role in the activation of members of the atypical CDK14-18 subfamily is established, its function in systemic metabolism remains poorly defined. Here, we report that CCNY overexpression drives a fatal metabolic syndrome. Using a novel inducible knock-in mouse model, we demonstrate that CCNY overexpression causes severe cachexia and profound hypoglycemia, resulting in death of adult mice independent of tumor burden. While these mutant mice maintain normal food intake and hepatic synthetic function, they succumb to metabolic starving state. Proteomics reveals that CCNY interacts with and stabilizes Pyruvate Dehydrogenase Kinase 4 (PDK4), in agreement with defective pyruvate use at mitochondria and enforcing a Warburg-like shift to aerobic glycolysis. Phosphoproteomic analysis indicates activation of apoptotic pathways and defective phosphorylation of several enzymes critical for glycolysis and gluconeogenesis as well as amino acid metabolism in addition to other metabolic routes. Altogether, these data suggest that CCNY overexpression uncouples nutrient sensing from utilization, a finding with possible therapeutic implications in CCNY-high cancers with similar changes in metabolic pathways.

cell biology↗

bioRxiv2025

Classification of Human Transcription Factors Based on Their Effector Domains via Unsupervised Learning

TFs combine DBDs, which anchor them to DNA, with EDs that regulate transcription through activation or repression, yet the sequence logic linking ED composition to function remains unclear. Here, we systematically define proxy regions--disordered segments adjacent to DBDs--to enable quantitative analysis of ED-like sequences across the human TF repertoire. Using a biophysically interpretable 22-feature classifier (FALK22) together with an embedding-based model (ESM), we map ED diversity and identify composition and charge-pattern signatures that correspond to regulatory activity along a disorder continuum, separating activation-from repression-associated regions. FALK22 identified classes align well with those identified from ESM while providing transparent, sequence-level features. Proxy regions near C-termini exhibit gradients that track DBD families, suggesting that EDs and DBDs might have co-evolved rather than evolved independently. These results establish proxy regions and FALK22 as a framework to connect sequence features with transcriptional activity and to generate testable hypotheses about effector-domain function and co-evolution with DNA-binding domains. HIGHLIGHTSO_LIWe define proxy regions as systematically identified disordered segments adjacent to DNA-binding domains (DBD), enabling quantitative analysis of effector domain (ED)-like sequences across the human transcription factor (TF) repertoire. C_LIO_LIWe develop FALK22, a 22-feature classification algorithm that classifies transcription factors based on simple sequence properties of their EDs and shows strong alignment with complex embedding-based representations from the Evolutionary Scale Model (ESM). C_LIO_LIFALK22 and ESM uncover distinct amino-acid composition and patterning signatures of EDs that correlate with transcriptional function, separating activation- and repression-associated regions along a disorder continuum. C_LIO_LIProxy regions located at the C-termini exhibit gradients that correspond to their DBD families, suggesting that EDs did not evolve as independent modular units but rather co-evolved with, or became selectively matched to, their DBD contexts. C_LI

bioinformatics↗

bioRxiv2024

miR-203 controls timing of developmental transitions during early preimplantation embryogenesis

Commonly expressed at developmental transitions, microRNAs operate as fine tuners of gene expression to facilitate cell fate acquisition and lineage segregation. Nevertheless, how they might regulate the earliest developmental transitions in early mammalian embryogenesis remains obscure. Here, in a strictly in vivo approach based on novel genetically-engineered mouse models and single-cell RNA sequencing, we identify miR-203 as a critical regulator of timing and cell fate restriction within the totipotency to pluripotency transition in mouse embryos. Genetically engineered mouse models show that loss of miR-203 slows down developmental timing during preimplantation leading to the accumulation of embryos with high expression of totipotency-associated markers, including MERVL endogenous retroviral elements. A new embryonic reporter (eE-Reporter) transgenic mouse carrying MERVL-Tomato and Sox2-GFP transgenes showed that lack of miR-203 leads to sustained expression of MERVL and reduced Sox2 expression in preimplantation developmental stages. A combination of single-cell transcriptional studies and epigenetic analyses identified the central coactivator and histone acetyltransferase P300 as a major miR-203 target at the totipotency to pluripotency transition in vivo. By fine tuning P300 levels, miR-203 carves the epigenetic rewiring process needed for this developmental transition, allowing a timely and correctly paced development.

developmental biology↗

bioRxiv2024

An integrated technology for quantitative wide mutational scanning of human antibody Fab libraries

Antibodies are engineerable quantities in medicine. Learning antibody molecular recognition would enable the in silico design of high affinity binders against nearly any proteinaceous surface. Yet, publicly available experiment antibody sequence-binding datasets may not contain the mutagenic, antigenic, or antibody sequence diversity necessary for deep learning approaches to capture molecular recognition. In part, this is because limited experimental platforms exist for assessing quantitative and simultaneous sequence-function relationships for multiple antibodies. Here we present MAGMA-seq, an integrated technology that combines multiple antigens and multiple antibodies and determines quantitative biophysical parameters using deep sequencing. We demonstrate MAGMA-seq on two pooled libraries comprising mutants of ten different human antibodies spanning light chain gene usage, CDR H3 length, and antigenic targets. We demonstrate the comprehensive mapping of potential antibody development pathways, sequence-binding relationships for multiple antibodies simultaneously, and identification of paratope sequence determinants for binding recognition for broadly neutralizing antibodies (bnAbs). MAGMA-seq enables rapid and scalable antibody engineering of multiple lead candidates because it can measure binding for mutants of many given parental antibodies in a single experiment.

biochemistry↗