ArticlemBio2021
Intra-Ramanome Correlation Analysis Unveils Metabolite Conversion Network from an Isogenic Population of Cells.
Article in mBio, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 24 citations in OpenAlex.
- Structural, Compositional, and Dielectric State Profiling in Label-Free Single-Cell Monitoring.Small methods · 2026Review
- Ecology-microbiome engineering in Sauce-flavor Baijiu via Single-Cell Raman Spectroscopy.Biodesign research · 2026Review
- Genotypic and Phenotypic Characterisation ofPathogens (Basel, Switzerland) · 2026Article
- RamEx: an R package for high-throughput microbial ramanome analyses with accurate quality assessment.Microbiome · 2026Article
- Profiling the heterogeneity of microbial populations and communities at the single-cell level.mLife · 2025Review
- Raman flow cytometry based single-cell species classification, viable-cell counting and vitality test for probiotic products.iMetaOmics · 2025Article
- Label-free high-throughput live-cell sorting of genome-wide random mutagenesis libraries for metabolic traits by Raman flow cytometry.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- A Single-Cell Metabolic Profiling Characterizes Human Aging via SlipChip-SERS.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- SERSomes for metabolic phenotyping and prostate cancer diagnosis.Cell reports. Medicine · 2024Article
- Robust Spontaneous Raman Flow Cytometry for Single-Cell Metabolic Phenome Profiling via pDEP-DLD-RFC.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023Article
- An attempt to simultaneously quantify the polysaccharide, total lipid, protein and pigment in single Cyclotella cryptica cell by Raman spectroscopy.Biotechnology for biofuels and bioproducts · 2023Article
- Single-cell Raman-activated sorting and cultivation (scRACS-Culture) for assessing and mining in situ phosphate-solubilizing microbes from nature.ISME communications · 2022Article
- Assessing Efficacy of Clinical Disinfectants for Pathogenic Fungi by Single-Cell Raman Microspectroscopy.Frontiers in cellular and infection microbiology · 2022Article
- Identification of pathogens and detection of antibiotic susceptibility at single-cell resolution by Raman spectroscopy combined with machine learning.Frontiers in microbiology · 2022Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
To reveal the dynamic features of cellular systems, such as the correlation among phenotypes, a time or condition series set of samples is typically required. Here, we propose intra-ramanome correlation analysis (IRCA) to achieve this goal from just one snapshot of an isogenic population, via pairwise correlation among the cells of the thousands of Raman peaks in single-cell Raman spectra (SCRS), i.e., by taking advantage of the intrinsic metabolic heterogeneity among individual cells. For example, IRCA of Chlamydomonas reinhardtii under nitrogen depletion revealed metabolite conversions at each time point plus their temporal dynamics, such as protein-to-starch conversion followed by starch-to-triacylglycerol (TAG) conversion, and conversion of membrane lipids to TAG. Such among-cell correlations in SCRS vanished when the starch-biosynthesis pathway was knocked out yet were fully restored by genetic complementation. Extension of IRCA to 64 microalgal, fungal, and bacterial ramanomes suggests the IRCA-derived metabolite conversion network as an intrinsic metabolic signature of isogenic cellular population that is reliable, species-resolved, and state-sensitive. The high-throughput, low cost, excellent scalability, and general extendibility of IRCA suggest its broad applications.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.