Andrea Petretto

Deep-coverage, high-throughput single-cell metabolomics - Nature Methods Current single-cell metabolomics methods show low sensitivity and limited coverage of small-molecule metabolites. We developed an ion mobility-resolved mass cytometry technology that incorporates selective ion accumulation and cell superposition strategies to deliver high sensitivity and deep coverage, which captured over 5,000 metabolic peaks and about 800 metabolites from individual cells in a high-throughput manner.

Deep-coverage, high-throughput single-cell metabolomics #nature #MassSpecRSS

Bluesky Map Interactive map of 3.4 million Bluesky users, visualised by their follower pattern.

I made a map of 3.4 million Bluesky users - see if you can find yourself!

bluesky-map.theo.io

I've seen some similar projects, but IMO this seems to better capture some of the fine-grained detail

Small volumes, deep insights: Longitudinal EV multi-omics in very preterm infants Introduction. Very preterm birth (<32 weeks of gestation) disrupts key developmental programs and exposes infants to a highly vulnerable postnatal period. However, the molecular trajectories underlyin...

www.medrxiv.org/content/10.6...

Fig. 4: Cross-omics network integration identifies coordinated EV proteomic-lipidomic modules. (a) Schematic overview of the cross-omics integration strategy. Temporally regulated EV proteins (n = 875) and lipids (n = 100), identified by longitudinal linear mixed-effects modeling (LMM), were integrated using a protein-lipid correlation network based on Spearman correlations across paired longitudinal samples. Louvain community detection was applied to identify cross-omics modules, which were subsequently tested for associations with clinical outcomes. (b) Distribution of Spearman correlation coefficients for protein-lipid pairs retained in the network after multiple-testing correction and effect-size filtering (|ρ|>0.35). Positive and negative correlations are shown separately, highlighting a structured and bimodal distribution of inter-omic associations. (c) Protein and lipid composition of the five cross-omics modules (M1-M5). Bars indicate the relative contribution of proteins and lipids within each module, with total node counts reported above each bar. (d) Functional annotation of protein components within each module based on Gene Ontology Biological Process enrichment analysis. Bars represent −log10(FDR) values for selected enriched terms, highlighting distinct biological themes across modules, including protein turnover, immune-related processes, translation, and extracellular matrix remodeling.

Integrated EV multi-omics reveals more than any single layer: • Quantified 1,528 proteins & 421 lipids. • Cross-omics modules show coordinated shifts in immune maturation. • Molecular trajectories correlate with brain injury & clinical outcomes. 3/3

We applied this method to a longitudinal cohort of very preterm infants of plasma per sample.
By tracking the molecular cargo of EVs from birth to term-equivalent age, we’ve captured the structured remodeling of the neonatal "liquid biopsy" during a critical developmental window. 2/3

Fig. 1: Longitudinal study design and plasma EV multi-omics profiling in very preterm infants. (a) Overview of the longitudinal cohort, sampling timeline, and analytical workflow. Plasma samples were collected from very preterm infants born at <32 weeks of gestational age (n = 16) at five time points from birth to term-equivalent age: at birth (T0), 48-72 hours of life (T1), 7 days of life (T2), 33 weeks postmenstrual age (PMA, T3), and 40 weeks PMA (T4, n = 10). EVs were enriched from plasma, followed by parallel isolation of EV-associated proteins and lipids from the same sample. Proteomic and lipidomic analyses were performed by LC-MS/MS, with raw data processed using dedicated pipelines prior to downstream statistical analyses. (b) Dynamic range of the plasma EV proteome, shown as a rank-abundance plot of median log₂ protein abundance across all samples, with selected EV-associated proteins highlighted. (c) Subcellular localization enrichment of the EV proteome based on the Jensen COMPARTMENTS database. Terms are ordered by the number of associated proteins along the x axis (protein count). Dot size reflects statistical significance (−log10 FDR), while color intensity indicates odds ratio. (d) Distribution of identified lipid species across major lipid classes, grouped into glycerophospholipids, glycerolipids, sphingolipids, fatty acyls, and sterol lipids.

"Dwarfs on the shoulders of giants"
We adapted the MacCoss group’s Mag-Net workflow to enable integrated protein & lipid profiling from the same EV preparation. This simple, effective shift uses 10 µL of plasma to study pathophysiology through minimal sample volumes.
1/3

MetaXtract: Extracting Metadata from Raw Files for FAIR Data Practices and Workflow Optimisation www.biorxiv.org/cont...

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#proteomics #prot-preprint

Current efforts focus on predicting transcriptional responses to gene silencing.

Even if spectacularly successful, they leave open key questions:
◾️Functions of genetic mutations & polymorphisms
◾️Proteoform functions
◾️Protein abundance regulation

Biology is complex.

Can we all agree to write all the grants in the first semester so we can do other things during the second semester?

thanks! but for the heat? This, for me, is a huge problem..

This is the typical solution for noise. Otherwise, you can put the pumps behind a wall.
Noise reduction box for your vacuum pump share.google/INWVOMRy4bH9...

We're planning the new labs at my institute. I'd be interested in anyone's suggestions on how to manage noise and heat from the pumps :)

Pretty cool update from GlycoScape:
Sugar-specific visualisation, based on the sugar type. Should help for hypothesis generation since you can plot each sugar type and compare.

Out in @cp-cellsystems.bsky.social‬: Deep Visual Proteomics shows xenotransplantation drives colon #organoids toward in-vivo-like proteomes supporting their use in regenerative medicine; culture tweaks can mimic this shift. With @kimbakjensen.bsky.social. Lead author Frederik Post explains below:

I want to start a new global movement:
Meetless Monday - we encourages people to reduce their meeting activity by one day each week for personal health and the planet's well-being.

News in Proteomics Research blog post | Mass spectrometry proteomics - From single cells through new(!) clinical applications! proteomicsnews.blogs...

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#proteomics #prot-other

Scalable Acid-Aided Lysis of Skin Samples Improves Proteome Coverage www.sciencedirect.co...

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#proteomics #prot-paper

Computational mass spectrometry for exposomics in non‑target screening - Analytical and Bioanalytical Chemistry

(ABioanChem) Computational mass spectrometry for exposomics in non‑target screening #MassSpecRSS

QuickProt: A Bioinformatics and Visualization Tool for DIA and PRM Mass Spectrometry‐Based Proteomics Datasets PROTEOMICS, EarlyView.

(Proteomics) QuickProt: A Bioinformatics and Visualization Tool for DIA and PRM Mass Spectrometry‐Based Proteomics Datasets: PROTEOMICS, EarlyView. #MassSpecRSS

His website is equally amazing, especially the haikus

hairyfatguy.com/lutefisk/

📢 Happy to announce that Ensembl 115 and Ensembl Genomes 62 are out! This release features ~120000 new protein coding transcripts in human GRCh38, 2 new cattle, 7 new plants and 20 new metazoa! 🧬🐮 🫛🪲
Read more here ➡️ zurl.co/poyXM

This provocative article does not mince words.

The authors argue that genome sequencing and scRNA-seq yield findings challenging the notion that cancer is a ‘genetic disease’:

"... the cancer research community has abandoned deep thinking for deep sequencing"

1/n

Liquid Chromatographic and Mass Spectrometric Methods for Quantitative Proteomic Analysis from Single-Cell and Nanogram-Level Samples pubs.acs.org/doi/10....

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#proteomics #prot-paper

Nice to see our SUGA approach on PanoramaWeb. It hosts our raw files and Skyline assays, to improve data analysis reproducibility.
Quick and easy N-glycomics, suitable for those trying out glycan analysis without spending extra $ on anything except PNGase-F!
Paper: pubmed.ncbi.nlm.nih.gov/39978775/

How to Apply Learn more about our application process

If you are interested in scientific software engineering or experimental work in the fields of spatial and multi-modal -omics, high throughput interaction proteomics, or mass instrumentation, apply until Oct 7th! @mannlab.bsky.social
www.biochem.mpg.de/mann
imprs-ml.mpg.de/How-to-Apply

Metagenomics and metabolomics to evaluate the potential role of gut microbiota and blood metabolites in patients with cerebral infarction - BMC Microbiology Cerebral infarction, a cerebrovascular disorder, is characterized by the sudden onset of neurological deficits and clinical symptoms. It ranks among the leading causes of death and severe disability w...

Metagenomics and metabolomics to evaluate the potential role of gut microbiota and blood metabolites in patients with cerebral infarction #BMCMicrobiol #MassSpec bmcmicrobiol.biomedcentral.com/articles/10....

Knowledge and data-driven two-layer networking for accurate metabolite annotation in untargeted metabolomics - Nature Communications Accurate metabolite annotation remains a major challenge in untargeted metabolomics. Here, the authors present MetDNA3, a framework that integrates knowledge and data-driven two-layer networking to improve both the accuracy and coverage of known metabolite annotation, while also enabling the discovery of uncharacterized metabolites.

Knowledge and data-driven two-layer networking for accurate metabolite annotation in untargeted metabolomics #nature #MassSpecRSS

[ASAP] Simulating Collision-Induced Dissociation Tandem Mass Spectrometry (CID-MS/MS) for the Blood Exposome Database Using Quantum Chemistry Methods - A Pilot Study Journal of the American Society for Mass SpectrometryDOI: 10.1021/jasms.5c00179

(JASMS) [ASAP] Simulating Collision-Induced Dissociation Tandem Mass Spectrometry (CID-MS/MS) for the Blood Exposome Database Using Quantum Chemistry Methods - A Pilot Study: Journal of the American Society for Mass SpectrometryDOI: 10.1021/jasms.5c00179 (RSS) #MassSpecRSS #JASMS

[ASAP] A Chromatography-Guided Co-Fractionation Mass Spectrometry Strategy for Rapid Profiling of Drug-Perturbed Protein Complexes Analytical ChemistryDOI: 10.1021/acs.analchem.5c02702

(ACS Anal Chem) [ASAP] A Chromatography-Guided Co-Fractionation Mass Spectrometry Strategy for Rapid Profiling of Drug-Perturbed Protein Complexes: Analytical ChemistryDOI: 10.1021/acs.analchem.5c02702 #MassSpecRSS #ACSAChem

Integration of cell-type resolved spatial proteomics and transcriptomics reveals novel mechanisms in early ovarian cancer High-grade serous carcinoma (HGSC) is the most common ovarian cancer subtype, typically diagnosed at late stages with poor prognosis. Understanding early molecular events driving HGSC progression is c...

Spatial proteomics & transcriptomics chart #ovariancancer evolution from fallopian tube precursors. Deep Visual Proteomics reveals early SUMOylation, TRIP13 epithelial driver, BGN therapeutic target & epithelial-stromal cooperation in progression.
www.medrxiv.org/content/10.1...