Single-cell proteomics by mass spectrometry (MS) allows quantifying proteins with high specificity and sensitivity. To increase its throughput, we developed nPOP, a method for parallel preparation of thousands of single cells in nanoliter volume droplets deposited on glass slides. Here, we describe its protocol with emphasis on its flexibility to prepare samples for different multiplexed MS methods. An implementation with plexDIA demonstrates accurate quantification of about 3,000 - 3,700 proteins per human cell. The protocol is implemented on the CellenONE instrument and uses readily available consumables, which should facilitate broad adoption. nPOP can be applied to all samples that can be processed to a single-cell suspension. It takes 1 or 2 days to prepare over 3,000 single cells. We provide metrics and software for quality control that can support the robust scaling of nPOP to higher plex reagents for achieving reliable high-throughput single-cell protein analysis. less

The aggressive nature of glioblastoma (GBM) - one of the deadliest forms of brain tumours - is majorly attributed to underlying phenotypic heterogeneity. Early attempts to classify this heterogeneity at a transcriptomic level in TCGA GBM cohort proposed the existence of four distinct molecular subtypes: Proneural, Neural, Classical and Mesenchymal. Further, a single-cell RNA-seq analysis of primary tumours also reported similar 4 subtypes mimicking neuro-developmental lineages. However, it remains unclear whether these 4 subtypes identified via bulk and single-cell transcriptomics are mutually exclusive or not. Here, we perform pairwise correlations among individual genes and gene signatures corresponding to these proposed subtypes, and show that the subtypes are not distinctly mutually antagonistic in either TCGA or single-cell RNA-sequencing data. We observed that the proneural (or neural progenitor-like) - mesenchymal axis is the most prominent antagonistic pair, with the other two subtypes lying on this spectrum. These results are reinforced through a meta-analysis of over 100 single-cell and bulk transcriptomic datasets as well as in terms of functional association with metabolic switching, cell cycle and immune evasion pathways. These results suggest rethinking GBM phenotypic characterization for more effective therapeutic targeting efforts. less

Targeted proteomics using multiple reaction monitoring (MRM) assays enables fast and sensitive detection of a preselected set of target peptides. This technique utilizes the specificity of precursors to product transitions for quantitative analysis of multiple proteins in a single sample. The success of an MRM experiment depends on the selection of transitions however, given the existing resources, accurately predicting signal intensity of peptides and their fragmentation patterns ab initio is challenging task. We present an alternative for rapid design of MRM transitions for proteomics research: DIGEST. Our method predicts the b and y ions with +1 and +2 charge produced in a collision cell of a mass spectrometer from peptides of multiple proteotypically digested proteins. Additionally, by using the existing knowledge of the fundamental rules for designing transitions, the tool provides optimal MRM transitions, negating the need to undertake prior discovery MS studies. We demonstrate that our algorithm is directed toward the selection of MRM precursor and product-ions pairs, and can avoid the pitfalls of interference due to cross-contamination of samples by selecting ion combinations that uniquely map to target peptides. Comparison with SRMAtlas showed that DIGEST successfully predicted the peptide and product-ion pairs in the majority of cases. We believe that DIGEST will facilitate rapid design of MRM assays with increased specificity, reducing the overall time required to design an MRM assay for routine mass-spectrometry. DIGEST is available as a web-based tool at https://digest.raylab.iiitd.edu.in/ less

Starch digestion is a cornerstone of human nutrition. The amylase enzyme, which digests starch, plays a key role in starch metabolism. Indeed, the copy number of the human amylase gene has been associated with metabolic diseases and adaptation to agricultural diets. Previous studies suggested that duplications of the salivary amylase gene are of recent origin. In the course of characterizing 51 distinct amylase haplotypes across 98 individuals employing long-read DNA sequencing and optical mapping methods, we detected four 31mers linked to duplication of the amylase locus. Analyses with these 31mers suggest that the first duplication of the amylase locus occurred more than 700,000 years ago before the split between modern humans and Neanderthals. After the original duplication events, amplification of the AMY1 genes likely occurred via nonallelic homologous recombination in a manner that consistently results in an odd number of copies per chromosome. These findings suggest that amylase haplotypes may have been primed for bursts of natural-selection associated duplications that coincided with the incorporation of starch into human diets. less

With the emergence of multidrug-resistant bacteria, the World Health Organization published a catalog of microorganisms in 2017 for which new antibiotics are urgently needed. Within this list, the carbapenem-resistant pathogen Acinetobacter baumannii, belonging to the ESKAPE group, has been granted the "critical" status. Over the years, such isolates have been detected within healthcare units, posing a global threat to upcoming pandemics. One way to facilitate a systemic view of bacterial metabolism and allow the development of new therapeutics based on environmental and genetic alterations is to apply constraint-based modeling on metabolic networks. We developed a versatile workflow to build high-quality and simulation-ready genome-scale metabolic models. We applied our workflow to create a novel metabolic model for A. baumannii and validated its predictive capabilities using experimental nutrient utilization and gene essentiality data. Our analysis showed that our model i ACB23LX could recapitulate cellular metabolic phenotypes observed during in vitro experiments with an accuracy of over 80%, while positive biomass production rates were observed in growth media relevant to A. baumannii. Additionally, we identified putative essential genes with no human counterparts, which could serve as novel antibiotic candidates for the development of future antimicrobial strategies. Finally, we have assembled the first curated collection of available reconstructions for distinct A. baumannii strains and analyzed their growth characteristics. The presented models herein are in a standardized and well-curated format, facilitating their usability, while they can be used to guide the reconstruction of multi-strain networks. Ultimately, they serve as a knowledge base for reliable predictions under various perturbations and the development of effective drugs. less

Animals must survive by foraging for food in an uncertain and dangerous world. Experimental tasks such as Pavlovian learning have yielded insights into how neural circuits balance these conflicting motivational drives. Neuromodulators play a fundamental role in this process, enabling flexible switching between motivational drives. The question of how neuromodulators synergistically encode motivational state is thus fundamental to systems neuroscience, yet the interplay between these neuromodulators during naturalistic decision making are not fully understood. Here, we developed a naturalistic approach/avoidance task in mice involving a tradeoff between seeking reward versus safety in the presence of looming predation risk. We utilized multi-fiber photometry, computational behavior tracking, and slice electrophysiology to understand the . Mice that experienced looming stimuli showed increased c-fos expression in regions including frontal cortex, locus coeruleus, and ventral tegmental area, but decreased expression in dorsal raphe nucleus. Moreover, by using multi-fiber photometry combined with GPCR-based sensors, we found that cortical norepinephrine (NE) plays a more prominent role in encoding looming threats while dopamine (DA) represents reward and threat. In contrast, serotonin (5HT) dynamic negatively correlates to both emotional valences. To begin to understand neuromodulatory intreractions, we used ex vivo slice physiology to understand 5HT impact on spontaneous firing of locus coeruleus NE neurons. In conclusion, monoamines such as NE, DA, 5HT can converge in their encoding of naturalistic motivated behaviors as well as dissociate from one another. By utilizing this approach, interactions between innate fear and incentive for food may be delineated in terms of basis in neurochemical signaling events during natural behavior, and may contribute to the understanding of neural mechanisms underlying emotional disorders including anxiety and post-traumatic stress disorder. less