Base by Base

Gustavo Barra

Base by Base explores advances in genetics and genomics, with a focus on gene-disease associations, variant interpretation, protein structure, and insights from exome and genome sequencing. Each episode breaks down key studies and their clinical relevance—one base at a time. Powered by AI, Base by Base offers a new way to learn on the go. Special thanks to authors who publish under CC BY 4.0, making open-access science faster to share and easier to explore.

  1. hace 14 h

    433: Lactate, HSP90α and the Mitochondrial Switch

    Wu G et al., Proceedings of the National Academy of Sciences - This episode examines a PNAS study that identifies site-specific lactylation of HSP90α as a metabolic signal linking glycolysis to mitochondrial biogenesis in ovarian cells. Lactylation at K58 and K616 modulates HSP90α phosphorylation, enabling nuclear import of PGC1α and LRPGC1, boosting mitochondrial number, cholesterol import, estradiol synthesis, and follicle growth; CREBBP, ACSS2 and GTPSCS participate in the lactylation pathway. Key terms: HSP90α, lactylation, PGC1α, mitochondrial biogenesis, estradiol. Study Highlights: The authors show that sodium lactate promotes HSP90α lactylation at K58 and K616 via CREBBP and lactyl-CoA synthesis (ACSS2/GTPSCS). K58 lactylation enhances ULK1 recruitment and S39 phosphorylation while K616 lactylation blocks CDK5-mediated S596 phosphorylation, together enabling HSP90α to chaperone PGC1α and LRPGC1 into the nucleus. Nuclear PGC1α/LRPGC1 activate NRF1/2 targets (Tfb1m, Tfb2m, Tfam) to drive mitochondrial biogenesis, increase mitochondrial cholesterol import and raise estradiol production, with in vivo lactate raising ovarian mtDNA, TOM20, estradiol and antral follicle number. Conclusion: Site-specific lactylation of HSP90α integrates glycolytic flux with chaperone and phosphorylation control to promote PGC1α/LRPGC1 nuclear import, mitochondrial biogenesis and steroidogenic output in ovarian cells, revealing a metabolite-dependent regulatory axis with potential implications for ovarian function and fertility. Music: Enjoy the music based on this article at the end of the episode. Article title: HSP90α lactylation orchestrates PGC1α and LRPGC1 nuclear translocation driving mitochondrial biogenesis First author: Wu G Journal: Proceedings of the National Academy of Sciences DOI: 10.1073/pnas.2528979123 Reference: Wu G., Li H., He T., et al. HSP90α lactylation orchestrates PGC1α and LRPGC1 nuclear translocation driving mitochondrial biogenesis. PNAS. 2026;123(30):e2528979123. doi:10.1073/pnas.2528979123 License: This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/ Support: Base by Base is independent and ad-free — no sponsors, no paywall. If an episode was worth your time, chip in and keep the papers audited and the original songs coming: ❤️ Support monthly: https://buy.stripe.com/cNifZhclVebvagk2JDgEg01 ☕ One-time donation: https://donate.stripe.com/7sY4gz71B2sN3RWac5gEg00 More at basebybase.com On PaperCast Base by Base you'll discover the latest in genomics, functional genomics, structural genomics, and proteomics. Episode link: https://basebybase.com/episodes/hsp90a-lactylation-mito-biogenesis QC: This episode was checked against the original article PDF and publication metadata for the episode release published on 2026-07-23. QC Scope: - article metadata and core scientific claims from the narration - excludes analogies, intro/outro, and music - transcript coverage: Audited the main mechanistic narrative from lactate signaling to HSP90α lactylation, ULK1/CDK5-regulated phosphorylation, nuclear import of PGC1α/LRPGC1, NRF1/2-driven transcription, mitochondrial biogenesis, cholesterol import, and in vivo hormonal/follicle outcomes. - transcript topics: Lactate as signaling molecule and lactylation concept; HSP90α lactylation at K58 and K616; CREBBP as the lactyltransferase and lactyl-CoA synthesis pathway; ULK1 and CDK5 regulation of S39 and S596 phosphorylation; HSP90α-mediated nuclear import of PGC1α and LRPGC1; NRF1/NRF2 target gene activation (TFB1M, TFB2M, Tfam) and mitochondrial biogenesis QC Summary: - factual score: 10/10 - metadata score: 10/10 - supported core claim...

  2. hace 14 h

    432: Echovirus 18: Capsid opening releases the genome

    Mukhamedova L et al., Proceedings of the National Academy of Sciences - Using cryo-electron tomography and single-particle cryo-EM of infected Cos-7 cells, the authors show that echovirus 18 (E18) releases its RNA in vivo by capsid opening with loss of one to three pentamers. Binding to the neonatal Fc receptor (FcRn) expels VP1 pocket factors and primes particles for uncoating. Activated intermediates were not detected in cells, indicating rapid genome release. Key terms: echovirus 18, enterovirus, genome release, capsid opening, FcRn. Study Highlights: Cryo-EM/ET of infected cells resolved genome-containing E18 particles to 4.3 Å and imaged empty and open capsids in situ. Binding of E18 to FcRn induces partial expulsion of VP1 pocket factors, consistent with receptor- triggered priming. Empty capsids observed inside cells lack one to three pentamers of capsid proteins, providing direct evidence of capsid opening as the genome release mechanism. Activated particles were not detected in cells, implying these intermediates are short- lived and genome release is rapid. Conclusion: Capsid opening is the physiological uncoating mechanism of echovirus 18 in infected cells: receptor (FcRn) binding expels pocket factors and primes particles, and genome release occurs rapidly via loss of one to several pentamers with empty, incomplete capsids observed in situ. Music: Enjoy the music based on this article at the end of the episode. Article title: Particles of echovirus 18 open to release their genomes in vivo First author: Mukhamedova L Journal: Proceedings of the National Academy of Sciences DOI: 10.1073/pnas.2601182123 Reference: Mukhamedova L., Buchta D., Hrebík D., et al. Particles of echovirus 18 open to release their genomes in vivo. PNAS. 2026;123(30):e2601182123. https://doi.org/10.1073/pnas.2601182123 License: This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/ Support: Base by Base is independent and ad-free — no sponsors, no paywall. If an episode was worth your time, chip in and keep the papers audited and the original songs coming: ❤️ Support monthly: https://buy.stripe.com/cNifZhclVebvagk2JDgEg01 ☕ One-time donation: https://donate.stripe.com/7sY4gz71B2sN3RWac5gEg00 More at basebybase.com On PaperCast Base by Base you'll discover the latest in genomics, functional genomics, structural genomics, and proteomics. Episode link: https://basebybase.com/episodes/echovirus-18-capsid-opening-432 QC: This episode was checked against the original article PDF and publication metadata for the episode release published on 2026-07-23. QC Scope: - article metadata and core scientific claims from the narration - excludes analogies, intro/outro, and music - transcript coverage: Audited the transcript sections describing E18 structure, FcRn binding and pocket-factor expulsion, endosomal acidification and detachment, in vivo evidence of empty/open capsids, and the genome release mechanism. - transcript topics: Echovirus 18 capsid structure and pocket factor; FcRn receptor binding and pocket-factor expulsion; Endocytosis and endosomal acidification as uncoating trigger; In vivo evidence: genome-containing particles lack pocket factors; Capsid opening with loss of one to three pentamers; Endosome rupture and cytoplasmic delivery of RNA QC Summary: - factual score: 10/10 - metadata score: 10/10 - supported core claims: 5 - claims flagged for review: 0 - metadata checks passed: 4 - metadata issues found: 0 Metadata Audited: - article_doi - article_title - article_journal - license Factual Items Audited: - In vivo, echovirus 18 genome release...

  3. hace 14 h

    431: KIAP4 and the ARND family: essential proteins for Leishmania–sand fly adhesion

    Owino BO et al., Proceedings of the National Academy of Sciences - TurboID proximity labeling and proteomics identify KIAP4 as the canonical member of a conserved Adhesion Related NTPase-like Domain (ARND) family that localizes to the Leishmania adhesion plaque. KIAP4 deletion disrupts haptomonad adhesion and prevents stomodeal valve colonization in sand flies. Key terms: Leishmania, adhesion, KIAP4, ARND family, vector colonization. Study Highlights: Using TurboID-tagged KIAP3 and mass spectrometry, the authors identified KIAP4 and multiple ARND family paralogs enriched at the adhered flagellum. KIAP4 localizes to the adhesion plaque alongside KIAP3 and accumulates during haptomonad differentiation. KIAP4 deletion severely reduces in vitro adhesion and abolishes stomodeal valve colonization in Lutzomyia longipalpis, while ARND paralogs are conserved and localize to adhered flagella in Trypanosoma congolense. Phylogenetic analysis shows ancient duplications and lineage-specific expansions of the ARND family across kinetoplastids. Conclusion: KIAP4 is a foundational adhesion-plaque protein and founding member of a conserved ARND family required for Leishmania haptomonad adhesion and sand fly stomodeal valve colonization, making ARND proteins candidate targets for transmission-blocking strategies. Music: Enjoy the music based on this article at the end of the episode. Article title: Identification of a conserved gene family with an essential role in Leishmania parasite–insect vector adhesion First author: Owino BO Journal: Proceedings of the National Academy of Sciences DOI: 10.1073/pnas.2603653123 Reference: Owino BO, Yanase R, Pruzinovac K, Farr H, Lopez Y, Marron AO, Vaughan S, Volf P, Sunter JD. Identification of a conserved gene family with an essential role in Leishmania parasite–insect vector adhesion. Proc Natl Acad Sci U S A. 2026;123(30):e2603653123. doi:10.1073/pnas.2603653123 License: This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/ Support: Base by Base is independent and ad-free — no sponsors, no paywall. If an episode was worth your time, chip in and keep the papers audited and the original songs coming: ❤️ Support monthly: https://buy.stripe.com/cNifZhclVebvagk2JDgEg01 ☕ One-time donation: https://donate.stripe.com/7sY4gz71B2sN3RWac5gEg00 More at basebybase.com On PaperCast Base by Base you'll discover the latest in genomics, functional genomics, structural genomics, and proteomics. Episode link: https://basebybase.com/episodes/kiap4-arnd-leishmania-adhesion QC: This episode was checked against the original article PDF and publication metadata for the episode release published on 2026-07-23. QC Scope: - article metadata and core scientific claims from the narration - excludes analogies, intro/outro, and music - transcript coverage: Audited spoken sections covering (1) identification of KIAP4 as the canonical ARND member and its adhesion-plaque localization, (2) TurboID proximity labeling methodology and protein enrichment results, (3) KIAP4 functional analyses including in vitro adhesion and in vivo valve colonization, (4) ARND conservation acros - transcript topics: KIAP4 and ARND identification in Leishmania; TurboID proximity labeling workflow and enrichment of adhesion-plaque components; Localization of KIAP4 and KIAP3 within the adhesion plaque; KIAP4 knockout effects on haptomonad adhesion and sand fly stomodeal valve colonization; ARND conservation across kinetoplastids (Trypanosoma congolense; T. brucei cross-species data); Inactive Walker A motif in ARND proteins (NTPase-like domains) QC Summary: - factual score: 10/10 - metadata score: 1...

  4. hace 14 h

    430: Proterozoic Rise: Steady Diversification of Crown Eukaryotes

    Sandin MM et al., Proceedings of the National Academy of Sciences - Molecular clocks and diversification models applied to a 75,975-OTU rDNA dataset, including long-read environmental sequences and 77 fossil calibrations, indicate crown-group eukaryotes diversified steadily from the mid‑Proterozoic with Archaeplastida dominating early diversity. Key terms: eukaryote evolution, Proterozoic diversification, Archaeplastida, molecular clock, environmental sequencing. Study Highlights: The study assembled 75,975 nonredundant rDNA OTUs combining long-read environmental metabarcoding and reference sequences and calibrated 32 timetrees with 77 fossil constraints. Molecular dating places LECA at ~1775 Ma and finds most eukaryotic supergroups originating across the Mesoproterozoic. Diversification analyses (ClaDS, BAMM) show steady accumulation of crown-group diversity through the Proterozoic, with Archaeplastida exhibiting an early rapid diversification likely tied to plastid endosymbiosis. Results suggest crown eukaryotes were ecologically and taxonomically diverse long before clear crown-group fossils appear. Conclusion: Integrating extensive environmental sequencing with molecular dating and diversification models reveals that crown-group eukaryotes were diversifying steadily from the mid‑Proterozoic, overturning the notion of a biologically stagnant “boring billion” and indicating early ecological interactions and endosymbioses drove diversification. Music: Enjoy the music based on this article at the end of the episode. Article title: Environmental phylogenetics supports a steady diversification of crown eukaryotes starting from the mid-Proterozoic First author: Sandin MM Journal: Proceedings of the National Academy of Sciences DOI: 10.1073/pnas.2600283123 Reference: Sandin MM, Burki F, Cohen PA, Morlond H (2026) Environmental phylogenetics supports a steady diversification of crown eukaryotes starting from the mid-Proterozoic. PNAS 123(29):e2600283123. doi:10.1073/pnas.2600283123 License: This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/ Support: Base by Base is independent and ad-free — no sponsors, no paywall. If an episode was worth your time, chip in and keep the papers audited and the original songs coming: ❤️ Support monthly: https://buy.stripe.com/cNifZhclVebvagk2JDgEg01 ☕ One-time donation: https://donate.stripe.com/7sY4gz71B2sN3RWac5gEg00 More at basebybase.com On PaperCast Base by Base you'll discover the latest in genomics, functional genomics, structural genomics, and proteomics. Episode link: https://basebybase.com/episodes/environmental-phylogenetics-steady-diversification-crown-eukaryotes QC: This episode was checked against the original article PDF and publication metadata for the episode release published on 2026-07-23. QC Scope: - article metadata and core scientific claims from the narration - excludes analogies, intro/outro, and music - transcript coverage: Audited transcript segments covering LECA dating and molecular clock; environmental sequencing (OTUs and 18S-28S rDNA); Archaeplastida endosymbiosis and early diversification; Proterozoic diversification dynamics and the 'boring billion' reinterpretation; predator–prey dynamics and fossil evidence; and limitations/samp - transcript topics: LECA dating and molecular clock; Environmental metabarcoding and OTU dataset (75,975 OTUs); Archaeplastida diversification and plastid endosymbiosis; Proterozoic diversification vs. 'boring billion' narrative; Predation, defense, and ecosystem dynamics (fossil evidence); Sampling limitations and diversification modeling (ClaDS, BAMM) QC Summary: - factual score: 10/10 - met...

  5. hace 14 h

    429: Validating the EAGL genetic literacy measure

    Barna LS et al., Human Genetics and Genomics Advances - We summarize a psychometric validation of the EAGL measure using US adult online samples. The study produced a validated 17-item EAGL-short that captures three core genetic literacy constructs and can be used to assess and target genetic communication and education. Key terms: genetic literacy, EAGL, psychometrics, knowledge comprehension, autism. Study Highlights: The authors administered the EAGL across three online US samples (combined N ≈ 2,708) and used exploratory and confirmatory factor analyses to refine the instrument. The final EAGL-short contains 17 items loading on three factors: subjective knowledge, knowledge comprehension, and conceptual (objective) knowledge, with CFA fit indices showing excellent model fit (CFI = 0.996, RMSEA = 0.031, SRMR = 0.080). Regression analyses found numeracy to be the strongest predictor across subscales, a personal connection to autism raised subjective familiarity but not comprehension or conceptual knowledge, and metropolitan vs non-metropolitan status showed no main effects. An interaction between education and connection to autism was observed for knowledge comprehension, highlighting education as a moderator. Conclusion: The EAGL-short is a psychometrically sound, 17-item tool that measures subjective knowledge, knowledge comprehension, and conceptual genetic knowledge in US adults; it enables more precise assessment of genetic literacy and the design of targeted educational interventions, though further validation in other languages and settings is recommended. Music: Enjoy the music based on this article at the end of the episode. Article title: Psychometric validation of the education and assessment of genetic literacy or the EAGL measure First author: Barna LS Journal: Human Genetics and Genomics Advances DOI: 10.1016/j.xhgg.2026.100651 Reference: Barna LS, Liao Y, Wierzbicki MR, Ramírez-Renta GM, Kaphingst KA, Gunter C. Psychometric validation of the education and assessment of genetic literacy or the EAGL measure. Human Genetics and Genomics Advances. 2026;7:100651. doi:10.1016/j.xhgg.2026.100651. License: This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/ Support: Base by Base is independent and ad-free — no sponsors, no paywall. If an episode was worth your time, chip in and keep the papers audited and the original songs coming: ❤️ Support monthly: https://buy.stripe.com/cNifZhclVebvagk2JDgEg01 ☕ One-time donation: https://donate.stripe.com/7sY4gz71B2sN3RWac5gEg00 More at basebybase.com On PaperCast Base by Base you'll discover the latest in genomics, functional genomics, structural genomics, and proteomics. Episode link: https://basebybase.com/episodes/eagl-psychometric-validation QC: This episode was checked against the original article PDF and publication metadata for the episode release published on 2026-07-23. QC Scope: - article metadata and core scientific claims from the narration - excludes analogies, intro/outro, and music - transcript coverage: Audited sections describing the EAGL-short validation, the three core constructs (subjective knowledge, knowledge comprehension, conceptual knowledge), the autism infographic for comprehension, numeracy as predictor, autism connection effects, metro geography findings, and education-autism interaction, plus implication - transcript topics: EAGL-short three-factor structure; Autism infographic used for knowledge comprehension; Numeracy as predictor of genetic literacy; Autism connection effects on subjective knowledge; Geography/metro status effects; Education and autism interaction affecting knowledge comprehension QC Summary:...

  6. hace 14 h

    428: Genetic regulation of plasma metabolites in people with HIV

    Ait Oumelloul M et al., Human Genetics and Genomics Advances - Untargeted plasma metabolomics (1,930 features) in 1,244 participants of the Swiss HIV Cohort Study were paired with genome-wide genotypes to map genetic influences on metabolite levels, test colocalization with eQTLs, and apply Mendelian randomization to probe causal links with aging-related biomarkers and diseases. Key terms: HIV, metabolomics, GWAS, Mendelian randomization, NAT8. Study Highlights: The study performed GWAS on 1,930 putative plasma metabolites measured by untargeted mass spectrometry in 1,244 people with HIV and identified 27 metabolites associated with 12 genetic loci, including NAT8, FUT2, PYROXD2, and FADS. Colocalization analyses found that 24 of the 27 metabolite loci overlapped with tissue eQTLs, linking genetic variants to gene expression and metabolite variation. Mendelian randomization using MR-link-2 provided evidence for putative causal relationships, notably genetically higher N-acetylcitrulline associated with lower serum creatinine (protective for kidney function) and chorismate linked to higher cholesterol and triglycerides. Sensitivity analyses across ancestries and sex and partial replication in non-HIV data supported the robustness of key signals. Conclusion: Integrating untargeted metabolomics with GWAS, eQTL colocalization, and MR in people with HIV revealed host genetic regulation of plasma metabolites, identified colocalized expression signals, and suggested causal links between specific metabolites and kidney and lipid biomarkers, highlighting targets for follow-up and the utility of multi-omics for precision comorbidity research in this population. Music: Enjoy the music based on this article at the end of the episode. Article title: Genome-wide association study of untargeted plasma metabolomic profiles identifies host genetic regulation in people with HIV First author: Ait Oumelloul M Journal: Human Genetics and Genomics Advances DOI: 10.1016/j.xhgg.2026.100635 Reference: Ait Oumelloul M, van der Graaf A, Tang S, Thorball CW, Labarile M, Saadat A, Timonina V, Schöpf IC, Wandeler G, Nemeth J, Cavassini M, Calmy A, Schmid P, Stöckle M, Elzi L, Zamboni N, Kouyos RD, Tarr PE, Fellay J; Swiss HIV Cohort Study. Genome-wide association study of untargeted plasma metabolomic profiles identifies host genetic regulation in people with HIV. Human Genetics and Genomics Advances. 2026;7:100635. https://doi.org/10.1016/j.xhgg.2026.100635 License: This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/ Support: Base by Base is independent and ad-free — no sponsors, no paywall. If an episode was worth your time, chip in and keep the papers audited and the original songs coming: ❤️ Support monthly: https://buy.stripe.com/cNifZhclVebvagk2JDgEg01 ☕ One-time donation: https://donate.stripe.com/7sY4gz71B2sN3RWac5gEg00 More at basebybase.com On PaperCast Base by Base you'll discover the latest in genomics, functional genomics, structural genomics, and proteomics. Episode link: https://basebybase.com/episodes/genetic-metabolomics-hiv-428 QC: This episode was checked against the original article PDF and publication metadata for the episode release published on 2026-07-23. QC Scope: - article metadata and core scientific claims from the narration - excludes analogies, intro/outro, and music - transcript coverage: Audited portions include study design and population, untargeted metabolomics, GWAS of metabolites, eQTL colocalization, Mendelian randomization analyses, and key metabolite–gene–disease links (NAT8/N-acetylcitrulline, chorismate, F11/5-HTP), along with limitations and clinical implications discussed in the transcrip...

  7. hace 14 h

    427: When Genes Talk to Gut: Microbiome as Mediator of Metabolic Risk

    Simpson RC et al., Trends in Genetics - This forum reviews evidence that host genetic variants associated with metabolic disease often overlap with loci that shape gut microbiome composition and function. Examples include LCT/MCM6 linking Bifidobacterium to reduced T2D risk, defensin locus variants affecting DEFA26 and Akkermansia abundance, and rs7133214 associating with HbA1c. The authors outline mechanisms, analytic tools, and experimental strategies to resolve causality and call for centralized microbiome–genetic resources. Key terms: gut microbiome, genetics, type 2 diabetes, defensins, bile acids. Study Highlights: The authors compile microbial GWAS loci and perform phenome-wide scans using the Synteny tool, revealing significant overlaps between microbe-associated SNPs and metabolic traits including obesity, HDL, blood glucose, and T2D. Case studies highlight loci such as LCT/MCM6, defensin genes (DEFA26–Akkermansia), and rs7133214 (methionine pathway) as examples of microbiome-mediated effects. Mechanisms likely include immune-mediated (Paneth cell defensins, NOD2, FUT2) and substrate/metabolite-mediated (lactose metabolism, bile acids, polyamines) pathways. The paper advocates integrated multi-omic studies, Mendelian randomisation, and human–mouse syntenic mapping, and emphasizes the need for a centralized database to enable causal inference. Conclusion: Host genetic control of the gut microbiome is widespread and may mediate many genetic links to metabolic disease; resolving causality will require integrated multi-omic datasets, improved causal-mapping tools, standardized databases, and complementary human and controlled mouse studies. Music: Enjoy the music based on this article at the end of the episode. Article title: The gut microbiome as an effector of metabolic disease gene variants First author: Simpson RC Journal: Trends in Genetics DOI: 10.1016/j.tig.2026.03.011 Reference: Simpson RC, Cutler HB, James DE, Masson SWC. The gut microbiome as an effector of metabolic disease gene variants. Trends in Genetics. 2026;42(7):585-588. https://doi.org/10.1016/j.tig.2026.03.011 License: This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/ Support: Base by Base is independent and ad-free — no sponsors, no paywall. If an episode was worth your time, chip in and keep the papers audited and the original songs coming: ❤️ Support monthly: https://buy.stripe.com/cNifZhclVebvagk2JDgEg01 ☕ One-time donation: https://donate.stripe.com/7sY4gz71B2sN3RWac5gEg00 More at basebybase.com On PaperCast Base by Base you'll discover the latest in genomics, functional genomics, structural genomics, and proteomics. Episode link: https://basebybase.com/episodes/genes-gut-microbiome-metabolic-variants QC: This episode was checked against the original article PDF and publication metadata for the episode release published on 2026-07-23. QC Scope: - article metadata and core scientific claims from the narration - excludes analogies, intro/outro, and music - transcript coverage: Substantively audited portions covering: (1) host genetic regulation of the gut microbiome and immune barrier, (2) specific gene–microbiome examples (LCT/MCM6, defensin locus, TCF7L2), (3) methodological approach (Synteny, CNV/MR concepts), (4) overlaps between microbial SNPs and human metabolic traits (HbA1c, HDL, obe - transcript topics: Gut microbiome as metabolic organ governed by host genetics; Lactase persistence (LCT/MCM6) and T2D risk via microbial metabolism; Defensin locus variants and Akkermansia muciniphila in mice; TCF7L2's role in Paneth cell development and dysbiosis; Synteny tool, microbial GWAS, and Mendelian randomisation conce...

  8. hace 14 h

    426: ProtoCloud — Prototypical self-explaining model for single-cell analysis

    Guo K et al., Cell Genomics - ProtoCloud is a self-explaining deep generative model that embeds single cells around cell-type-specific prototypes to deliver accurate, uncertainty-aware cell type annotation and gene-level explanations from raw UMI counts. Key terms: single-cell, explainable AI, prototypical models, cell type annotation, uncertainty estimation. Study Highlights: ProtoCloud achieves accurate and efficient annotation of single-cell data, including improved detection of rare cell types, by organizing embeddings around learned prototypes. A disentangled latent space separates biological identity from batch and nuisance variation, improving robustness and label transfer. Built-in uncertainty quantification based on cell–prototype similarity identifies and enables correction of misannotations. Prototypical relevance propagation backpropagates similarity to highlight genes driving classification for instant gene‑level explainability. Conclusion: By combining a decomposed VAE, learnable prototypes, PRP-based gene relevance, and calibrated similarity-based uncertainty, ProtoCloud provides accurate, interpretable, and robust single-cell annotations that detect rare states, correct label errors, and nominate marker genes to support atlas construction and disease studies. Music: Enjoy the music based on this article at the end of the episode. Article title: ProtoCloud: A prototypical self-explaining model for single-cell analysis First author: Guo K Journal: Cell Genomics DOI: 10.1016/j.xgen.2026.101217 Reference: Guo K. & Ding J. ProtoCloud: A prototypical self-explaining model for single-cell analysis. Cell Genomics 6, 101217 (2026). doi:10.1016/j.xgen.2026.101217 License: This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/ Support: Base by Base is independent and ad-free — no sponsors, no paywall. If an episode was worth your time, chip in and keep the papers audited and the original songs coming: ❤️ Support monthly: https://buy.stripe.com/cNifZhclVebvagk2JDgEg01 ☕ One-time donation: https://donate.stripe.com/7sY4gz71B2sN3RWac5gEg00 More at basebybase.com On PaperCast Base by Base you'll discover the latest in genomics, functional genomics, structural genomics, and proteomics. Episode link: https://basebybase.com/episodes/protocloud-prototypical-self-explaining-single-cell QC: This episode was checked against the original article PDF and publication metadata for the episode release published on 2026-07-23. QC Scope: - article metadata and core scientific claims from the narration - excludes analogies, intro/outro, and music - transcript coverage: Audited the transcript segments describing ProtoCloud architecture, training, uncertainty quantification, and key biological validations (PBMC, RGC time course, EoE). - transcript topics: ProtoCloud architecture and prototypes; Disentangled latent space with z1 and z2; Prototypical relevance propagation (PRP) and HRGs; Robustness to label noise (20% perturbation); PBMC30K annotation corrections (NKG7 example); Time-course retinal ganglion cells after optic nerve crush QC Summary: - factual score: 10/10 - metadata score: 10/10 - supported core claims: 7 - claims flagged for review: 0 - metadata checks passed: 4 - metadata issues found: 0 Metadata Audited: - article_doi - article_title - article_journal - license Factual Items Audited: - ProtoCloud uses six prototypes per cell type by default - Latent space is partitioned into two components: z1 for cell-type identity and z2 for batch/noise factors - PRP identifies gene-level relevance and HRGs (e.g., CD79B, LY9)...

Información

Base by Base explores advances in genetics and genomics, with a focus on gene-disease associations, variant interpretation, protein structure, and insights from exome and genome sequencing. Each episode breaks down key studies and their clinical relevance—one base at a time. Powered by AI, Base by Base offers a new way to learn on the go. Special thanks to authors who publish under CC BY 4.0, making open-access science faster to share and easier to explore.

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