Dual regulation of SLC25A39 by AFG3L2 and iron controls mitochondrial glutathione homeostasis.

Organelle transporters define metabolic compartmentalization, and how this metabolite transport process can be modulated is poorly explored. Here, we discovered that human SLC25A39, a mitochondrial transporter critical for mitochondrial glutathione uptake, is a short-lived protein under dual regulation at the protein level. Co-immunoprecipitation mass spectrometry and CRISPR knockout (KO) in mammalian cells identified that mitochondrial m-AAA protease AFG3L2 is responsible for degrading SLC25A39 through the matrix loop 1. SLC25A39 senses mitochondrial iron-sulfur cluster using four matrix cysteine residues and inhibits its degradation. SLC25A39 protein regulation is robust in developing and mature neurons. This dual transporter regulation, by protein quality control and metabolic sensing, allows modulating mitochondrial glutathione level in response to iron homeostasis, opening avenues for exploring regulation of metabolic compartmentalization. Neuronal SLC25A39 regulation connects mitochondrial protein quality control, glutathione, and iron homeostasis, which were previously unrelated biochemical features in neurodegeneration.

Phosphorylation of the nuclear poly(A) binding protein (PABPN1) during mitosis protects mRNA from hyperadenylation and maintains transcriptome dynamics.

Polyadenylation controls mRNA biogenesis, nucleo-cytoplasmic export, translation and decay. These processes are interdependent and coordinately regulated by poly(A)-binding proteins (PABPs), yet how PABPs are themselves regulated is not fully understood. Here, we report the discovery that human nuclear PABPN1 is phosphorylated by mitotic kinases at four specific sites during mitosis, a time when nucleoplasm and cytoplasm mix. To understand the functional consequences of phosphorylation, we generated a panel of stable cell lines inducibly over-expressing PABPN1 with point mutations at these sites. Phospho-inhibitory mutations decreased cell proliferation, highlighting the importance of PABPN1 phosphorylation in cycling cells. Dynamic regulation of poly(A) tail length and RNA stability have emerged as important modes of gene regulation. We therefore employed long-read sequencing to determine how PABPN1 phospho-site mutants affected poly(A) tails lengths and TimeLapse-seq to monitor mRNA synthesis and decay. Widespread poly(A) tail lengthening was observed for phospho-inhibitory PABPN1 mutants. In contrast, expression of phospho-mimetic PABPN1 resulted in shorter poly(A) tails with increased non-A nucleotides, in addition to increased transcription and reduced stability of a distinct cohort of mRNAs. Taken together, PABPN1 phosphorylation remodels poly(A) tails and increases mRNA turnover, supporting the model that enhanced transcriptome dynamics reset gene expression programs across the cell cycle.

Optimal conditions for carrying out trypsin digestions on complex proteomes: From bulk samples to single cells.

To identify proteins by the bottom-up mass spectrometry workflow, enzymatic digestion is essential to break down proteins into smaller peptides amenable to both chromatographic separation and mass spectrometric analysis. Trypsin is the most extensively used protease due to its high cleavage specificity and generation of peptides with desirable positively charged N- and C-terminal amino acid residues that are amenable to reverse phase HPLC separation and MS/MS analyses. However, trypsin can yield variable digestion profiles and its protein cleavage activity is interdependent on trypsin source and quality, digestion time and temperature, pH, denaturant, trypsin and substrate concentrations, composition/complexity of the sample matrix, and other factors. There is therefore a need for a more standardized, general-purpose trypsin digestion protocol. Based on a review of the literature we delineate optimal conditions for carrying out trypsin digestions of complex proteomes from bulk samples to limiting amounts of protein extracts. Furthermore, we highlight recent developments and technological advances used in digestion protocols to quantify complex proteomes from single cells. SIGNIFICANCE: Currently, bottom-up MS-based proteomics is the method of choice for global proteome analysis. Since trypsin is the most utilized protease in bottom-up MS proteomics, delineating optimal conditions for carrying out trypsin digestions of complex proteomes in samples ranging from tissues to single cells should positively impact a broad range of biomedical research.

A complex of the lipid transport ER proteins TMEM24 and C2CD2 with band 4.1 at cell-cell contacts.

Junctions between the ER and plasma membrane (PM) are implicated in calcium homeostasis, non-vesicular lipid transfer, and other cellular functions. Two ER proteins that function both as tethers to the PM via a polybasic C-terminus motif and as phospholipid transporters are brain-enriched TMEM24 (C2CD2L) and its paralog C2CD2. We report that both proteins also form a complex with band 4.1 family members, which in turn bind PM proteins including cell adhesion molecules such as SynCAM 1. This complex enriches TMEM24 and C2CD2 containing ER/PM junctions at sites of cell contacts. Dynamic properties of TMEM24-dependent ER/PM junctions are impacted when band 4.1 is part of the junction, as TMEM24 at cell-adjacent ER/PM junctions is not shed from the PM by calcium rise, unlike TMEM24 at non-cell adjacent junctions. Lipid transport between the ER and the PM by TMEM24 and C2CD2 at sites where cells, including neurons, contact other cells may participate in adaptive responses to cell contact-dependent signaling.

Microbiome Depletion Increases Fentanyl Self-Administration and Alters the Striatal Proteome Through Short-Chain Fatty Acids.

Opioid use disorder (OUD) is a public health crisis currently being exacerbated by increased rates of use and overdose of synthetic opioids, primarily fentanyl. Therefore, the identification of novel biomarkers and treatment strategies to reduce problematic fentanyl use and relapse to fentanyl taking is critical. In recent years, there has been a growing body of work demonstrating that the gut microbiome can serve as a potent modulator of the behavioral and transcriptional responses to both stimulants and opioids. Here, we advance this work to define how manipulations of the microbiome drive fentanyl intake and fentanyl-seeking in a translationally relevant drug self-administration model. Depletion of the microbiome of male rats with broad spectrum antibiotics leads to increased drug administration on increased fixed ratio, progressive ratio, and drug seeking after abstinence. Utilizing 16S  sequencing of microbiome contents from these animals, specific populations of bacteria from the gut microbiome correlate closely with levels of drug taking. Additionally, global proteomic analysis of the nucleus accumbens following microbiome manipulation and fentanyl administration to define how microbiome status alters the functional proteomic landscape in this key limbic substructure. These data demonstrate that an altered microbiome leads to marked changes in the synaptic proteome in response to repeated fentanyl treatment. Finally, behavioral effects of microbiome depletion are reversible by upplementation of the microbiome derived short-chain fatty acid metabolites. Taken together, these findings establish clear relevance for gut-brain signaling in models of OUD and lay foundations for further translational work in this space.

BERNN: Enhancing classification of Liquid Chromatography Mass Spectrometry data with batch effect removal neural networks.

Liquid Chromatography Mass Spectrometry (LC-MS) is a powerful method for profiling complex biological samples. However, batch effects typically arise from differences in sample processing protocols, experimental conditions, and data acquisition techniques, significantly impacting the interpretability of results. Correcting batch effects is crucial for the reproducibility of omics research, but current methods are not optimal for the removal of batch effects without compressing the genuine biological variation under study. We propose a suite of Batch Effect Removal Neural Networks (BERNN) to remove batch effects in large LC-MS experiments, with the goal of maximizing sample classification performance between conditions. More importantly, these models must efficiently generalize in batches not seen during training. A comparison of batch effect correction methods across five diverse datasets demonstrated that BERNN models consistently showed the strongest sample classification performance. However, the model producing the greatest classification improvements did not always perform best in terms of batch effect removal. Finally, we show that the overcorrection of batch effects resulted in the loss of some essential biological variability. These findings highlight the importance of balancing batch effect removal while preserving valuable biological diversity in large-scale LC-MS experiments.

Cell-specific cross-talk proteomics reveals cathepsin B signaling as a driver of glioblastoma malignancy near the subventricular zone.

Glioblastoma (GBM) is the most prevalent and aggressive malignant primary brain tumor. GBM proximal to the lateral ventricles (LVs) is more aggressive, potentially because of subventricular zone contact. Despite this, cross-talk between GBM and neural stem/progenitor cells (NSC/NPCs) is not well understood. Using cell-specific proteomics, we show that LV-proximal GBM prevents neuronal maturation of NSCs through induction of senescence. In addition, GBM brain tumor-initiating cells (BTICs) increase expression of cathepsin B (CTSB) upon interaction with NPCs. Lentiviral knockdown and recombinant protein experiments reveal that both cell-intrinsic and soluble CTSB promote malignancy-associated phenotypes in BTICs. Soluble CTSB stalls neuronal maturation in NPCs while promoting senescence, providing a link between LV-tumor proximity and neurogenesis disruption. Last, we show LV-proximal CTSB up-regulation in patients, showing the relevance of this cross-talk in human GBM biology. These results demonstrate the value of proteomic analysis in tumor microenvironment research and provide direction for new therapeutic strategies in GBM.