Lovell, B. | bioRxiv Science

bioRxiv2026

Disrupted mannosidase enzymes in C9orf72 ALS/FTD

Amyotrophic lateral sclerosis (ALS) is an age-related neurodegenerative disorder resulting from the loss of motor neurons in the brain and spinal cord. Neuroinflammation, induced by glial cells including microglia (MG) and astrocytes, is an acknowledged aspect of this neurodegeneration. Generating induced pluripotent stem cell (iPSC) neuroinflammatory models of ALS may help elucidate non-neuronal mechanisms of disease. Here, we analyze human postmortem tissue and an iPSC derived glia-crosstalk model identifying a reduction in Golgi enzymes MAN1A1 and MAN1A2 in addition to other glycan enzymes from ALS-associated microglia and astrocytes. Impaired Golgi and glycan metabolism is linked to inflammation and other related ALS disease mechanisms including impaired lysosomal proteostasis, altered extracellular matrix, disrupted secretion, and altered cell-cell signaling.

neuroscience↗

bioRxiv2026

Resolving Immune Lineage and Cell-State Heterogeneity in Human PBMCs via Mass Spectrometry-Based Single-Cell Proteomics

Single-cell proteomics (SCP) currently lacks validated benchmarking standards, and cell annotation often relies on transcriptomic proxies. Unsupervised clustering offers a proxy-free alternative, but its success depends on biological signal outweighing technical variation. In homogeneous samples this is achievable, but in heterogeneous populations, where closely related cell types differ only subtly, technical variation can dominate the clustering and obscure the biology needed for annotation. To address this, we developed an integrated experimental and computational pipeline for protein-level cell annotation and applied it to human PBMCs as an immune-cell test case. We isolated T cells, B cells, monocytes, and NK cells by negative-selection sorting to build a high-fidelity reference. In parallel, unsorted PBMCs from the same donor were processed on a cellenONE and acquired using label-free DIA on an Orbitrap Astral Zoom. Using the labeled reference dataset, we systematically benchmarked normalization, imputation, and clustering methods to assess their effect on cell-type separation. Unsupervised analysis resolved functional subpopulations within each lineage, and a probabilistic SCP classifier trained on these annotations identified the corresponding cell types and states in the unsorted PBMC fraction, validating the pipeline on unenriched, heterogeneous samples. Together, this work delivers an analytically benchmarked SCP workflow that resolves immune lineage and cell-state heterogeneity in human PBMCs and provides a classifier-ready, protein-level reference for immune-cell assignment.

bioinformatics↗