Biology subjects

Alfaro, J.

Publications and source records attributed to Alfaro, J..

5 recordsLinked to original sources

bioRxiv2026

Informatics Methods to Enhance Bacterial Peptide Detection

Detecting low-abundance bacterial peptides in samples dominated by human proteins using liquid chromatography tandem mass spectrometry (LC MS/MS) is challenging. Bacterial peptides are typically far less abundant than host-derived peptides, and sequence similarity between bacterial and human peptides can complicate confident attribution to a bacterial origin. To address this problem, we developed and benchmarked an in silico spectral library protein identification workflow for detecting Staphylococcus aureus USA300 peptides against a background of A375 cells. Peptide and protein identifications obtained at a 1% peptide-level false discovery rate were compared between the in silico spectral library search and a conventional sequence database search across a defined bacterial dilution series containing 0, 1%, 2%, 10%, 25%, 50%, and 100% bacterial protein. A human sequence similarity filter was applied to identifications from both search strategies to reduce the likelihood of retaining human derived or human like peptide sequences. Both search strategies showed concentration dependent bacterial detection and shared a practical detection limit of approximately 1 to 2% bacterial protein but exhibited distinct performance profiles. The in silico spectral library search produced fewer bacterial-like background identifications in the human-only control, whereas MS2Rescore substantially increased spectral library identifications at higher bacterial concentrations, exceeding database search at 100% bacterial protein. The partially overlapping peptide sets identified by the two strategies indicate that they provide complementary coverage of the bacterial proteome.

biochemistry↗

bioRxiv2026

Deep Learning-Based Structure Modeling of the Treponema pallidum Proteome: Insights into Pathogenesis and Syphilis Vaccine Development

Treponema pallidum ssp. pallidum, the causative agent of syphilis, has a small proteome and encompasses numerous strains. Knowledge gaps remain in understanding the molecular mechanisms of pathogenesis of this bacterium, as well as the structure and function of the full complement of proteins encoded by T. pallidum. Here, an AI-based structure-to-function modeling workflow was used to investigate the complement of proteins encoded by T. pallidum. High-confidence structure models were generated for 976 T. pallidum proteins, covering 99% of the proteome. Analysis of the generated models using the protein structure comparison server DALI enabled high-confidence, structure-based functional annotation of 877 T. pallidum proteins, including 240 of the 323 proteins of unknown function encoded by this pathogen. Additionally, 63 putative pathogenesis related proteins (PPRPs) and seven treponemal proteins with previously uncharacterized similarity to outer membrane proteins (OMPs) from Gram-negative bacteria were identified. A workflow for B cell epitope (BCE) prediction identified 1133 surface-exposed, host-facing potential epitopes in known and predicted T. pallidum OMPs, of which 92 were prioritized based on bioinformatic analyses, biophysical properties, amino acid sequence conservation, and previous protein expression data. This work provides insight into T. pallidum pathogenesis through structure modeling-based functional annotation, including characterization of proteins of unknown function. This study also informs syphilis vaccine design by identifying new potential T. pallidum OMPs, as well as host-facing regions of T. pallidum OMPs that have conserved amino acid sequences in globally circulating strains. Statement of importance/impactThis study presents the first AI-based global structure modeling-to-function analysis of the proteome of Treponema pallidum, the bacterium that causes syphilis. Structure-based functional predictions of previously uncharacterized proteins, including proteins potentially involved in virulence, provide novel insight into mechanisms of pathogenesis. The work also informs syphilis vaccine development by the identification and structural characterization of new candidate vaccine proteins in globally circulating strains of T. pallidum.

microbiology↗

bioRxiv2024

Truncated TrkB: The predominant TrkB Isoform in Nociceptors

Truncated TrkB (TrkBT1), traditionally considered a dominant-negative regulator of full-length TrkB (TrkBTK+), remains poorly understood in peripheral sensory neurons, particularly nociceptors. Furthermore, sensory neuronal TrkB expression and function has been traditionally associated with non-nociceptive neurons, particularly A{delta} low-threshold mechanoreceptors. This study challenges prevailing assumptions by demonstrating that TrkBT1 is the predominant TrkB isoform expressed in sensory neurons and plays a functional role in modulating neuronal activity. We demonstrate that TrkBT1 is the predominant isoform expressed in nociceptors, identified by markers such as TRPV1, TRPA1, TRPM8 and 5HT3A, as well as non-nociceptors, while the full-length isoform (TrkBTK+) is restricted to non-nociceptive subpopulation. Functionally, we show that acute application of BDNF induces modest calcium influx in nociceptors and prolonged BDNF exposure significantly potentiates capsaicin-induced calcium influx, an effect blocked by the TrkB-specific antagonist ANA12. Additionally, BDNF also promotes the survival of both nociceptive and non-nociceptive neurons in culture, an effect dependent on TrkBT1 activity. Our data also reveal that ANA12 inhibits BDNF-mediated neuronal sensitization and survival in a concentration-dependent manner, implicating distinct TrkBT1 signaling pathways in these processes. Collectively, our findings redefine TrkBT1 as a functional modulator of nociceptor activity rather than a passive regulator of full-length TrkB. By uncovering its dual roles in nociceptor sensitization and survival, this study provides new insights into the molecular mechanisms of BDNF/TrkB signaling in pain. Future work evaluating the role of TrkBT1 in sensory biology could offer new perspectives on how this receptor contributes to neuronal function and plasticity during chronic pain conditions.

neuroscience↗

bioRxiv2023

Utility of language model and physics-based approaches in modifying MHC Class-I immune-visibility for the design of vaccines and therapeutics

Proteins have an arsenal of medical applications that include disrupting protein interactions, acting as potent vaccines, and replacing genetically deficient proteins. While therapeutics must avoid triggering unwanted immune-responses, vaccines should support a robust immune-reaction targeting a broad range of pathogen variants. Therefore, computational methods modifying proteins immunogenicity without disrupting function are needed. While many components of the immune-system can be involved in a reaction, we focus on Cytotoxic T-lymphocytes (CTLs). These target short peptides presented via the MHC Class I (MHC-I) pathway. To explore the limits of modifying the visibility of those peptides to CTLs within the distribution of naturally occurring sequences, we developed a novel machine learning technique, CAPE-XVAE. It combines a language model with reinforcement learning to modify a proteins immune-visibility. Our results show that CAPE-XVAE effectively modifies the visibility of the HIV Nef protein to CTLs. We contrast CAPE-XVAE to CAPE-Packer, a physics-based method we also developed. Compared to CAPE-Packer, the machine learning approach suggests sequences that draw upon local sequence similarities in the training set. This is beneficial for vaccine development, where the sequence should be representative of the real viral population. Additionally, the language model approach holds promise for preserving both known and unknown functional constraints, which is essential for the immune-modulation of therapeutic proteins. In contrast, CAPE-Packer, emphasizes preserving the proteins overall fold and can reach greater extremes of immune-visibility, but falls short of capturing the sequence diversity of viral variants available to learn from. Source code: https://github.com/hcgasser/CAPE (Tag: CAPE 1.1)

bioinformatics↗

bioRxiv2019

The Eya1 phosphatase mediates Shh-driven symmetric cell division of cerebellar granule cell precursors

During neural development, stem and precursor cells can divide either symmetrically or asymmetrically. The transition between symmetric and asymmetric cell divisions is a major determinant of precursor cell expansion and neural differentiation, but the underlying mechanisms that regulate this transition are not well understood. Here, we identify the Sonic hedgehog (Shh) pathway as a critical determinant regulating the mode of division of cerebellar granule cell precursors (GCPs). Using partial gain and loss of function mutations within the Shh pathway, we show that pathway activation determines spindle orientation of GCPs, and that mitotic spindle orientation directly correlates with the mode of division. Mechanistically, we show that the phosphatase Eya1 is essential for implementing Shh-dependent GCP spindle orientation. We identify atypical protein kinase C (aPKC) as a direct target of Eya1 activity and show that Eya1 dephosphorylates Threonine (T410) in the activation loop of this polarity complex component. Thus, Eya1 inactivates the cell polarity complex, resulting in reduced phosphorylation of Numb and other components that regulate the mode of division. This Eya1-dependent cascade is critical in linking spindle orientation, cell cycle exit and terminal differentiation. Together these findings demonstrate that a Shh-Eya1 regulatory axis selectively promotes symmetric cell divisions during cerebellar development by coordinating spindle orientation and cell fate determinants.\n\nSummary statementBiological responses to Shh signaling are specified by the magnitude of pathway activation and the cellular context. This study shows that potent Shh signaling regulates mitotic orientation and symmetric division of cerebellar granule cell precursors in a process that requires the phosphatase Eya1 and unequal distribution of cell fate determinants to daughter cells.

neuroscience↗