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Machine learning approaches reveal subtle differences in breathing and sleep fragmentation in Phox2b-derived astrocytes ablated mice.
No full textModern neurophysiology research requires the interrogation of high-dimensionality data sets. Machine learning and artificial intelligence (ML/AI) workflows have permeated into nearly all aspects of daily life in the developed world but have not been implemented routinely in neurophysiological analyses. The power of these workflows includes the speed at which they can be deployed, their availability of open-source programming languages, and the objectivity permitted in their data analysis. We used classification-based algorithms, including random forest, gradient boosted machines, support vector machines, and neural networks, to test the hypothesis that the animal genotypes could be separated into their genotype based on interpretation of neurophysiological recordings. We then interrogate the models to identify what were the major features utilized by the algorithms to designate genotype classification. By using raw EEG and respiratory plethysmography data, we were able to predict which recordings came from genotype class with accuracies that were significantly improved relative to the no information rate, although EEG analyses showed more overlap between groups than respiratory plethysmography. In comparison, conventional methods where single features between animal classes were analyzed, differences between the genotypes tested using baseline neurophysiology measurements showed no statistical difference. However, ML/AI workflows successfully were capable of providing successful classification, indicating that interactions between features were different in these genotypes. ML/AI workflows provide new methodologies to interrogate neurophysiology data. However, their implementation must be done with care so as to provide high rigor and reproducibility between laboratories. We provide a series of recommendations on how to report the utilization of ML/AI workflows for the neurophysiology community.NEW & NOTEWORTHY ML/AI classification workflows are capable of providing insight into differences between genotypes for neurophysiology research. Analytical techniques utilized in the neurophysiology community can be augmented by implementing ML/AI workflows. Random forest is a robust classification algorithm for respiratory plethysmography data. Utilization of ML/AI workflows in neurophysiology research requires heightened transparency and improved community research standards
Gene duplication at the Fascicled ear1 locus controls the fate of inflorescence meristem cells in maize.
No full textPlant meristems are self-renewing groups of pluripotent stem cells that produce lateral organs in a stereotypical pattern. Of interest is how the radially symmetrical meristem produces laminar lateral organs. Both the male and female inflorescence meristems of the dominant Fascicled ear (Fas1) mutant fail to grow as a single point and instead show deep branching. Positional cloning of two independent Fas1 alleles identified an ∼160 kb region containing two floral genes, the MADS-box gene, zmm8, and the YABBY gene, drooping leaf2 (drl2). Both genes are duplicated within the Fas1 locus and spatiotemporally misexpressed in the mutant inflorescence meristems. Increased zmm8 expression alone does not affect inflorescence development; however, combined misexpression of zmm8, drl2, and their syntenic paralogs zmm14 and drl1, perturbs meristem organization. We hypothesize that misexpression of the floral genes in the inflorescence and their potential interaction cause ectopic activation of a laminar program, thereby disrupting signaling necessary for maintenance of radially symmetrical inflorescence meristems. Consistent with this hypothesis, RNA sequencing and in situ analysis reveal altered expression patterns of genes that define distinct zones of the meristem and developing leaf. Our findings highlight the importance of strict spatiotemporal patterns of expression for both zmm8 and drl2 and provide an example of phenotypes arising from tandem gene duplications
Striatal dopamine mediates hallucination-like perception in mice.
No full textHallucinations, a central symptom of psychotic disorders, are attributed to excessive dopamine in the brain. However, the neural circuit mechanisms by which dopamine produces hallucinations remain elusive, largely because hallucinations have been challenging to study in model organisms. We developed a task to quantify hallucination-like perception in mice. Hallucination-like percepts, defined as high-confidence false detections, increased after hallucination-related manipulations in mice and correlated with self-reported hallucinations in humans. Hallucination-like percepts were preceded by elevated striatal dopamine levels, could be induced by optogenetic stimulation of mesostriatal dopamine neurons, and could be reversed by the antipsychotic drug haloperidol. These findings reveal a causal role for dopamine-dependent striatal circuits in hallucination-like perception and open new avenues to develop circuit-based treatments for psychotic disorders
Detection of Chemotherapy-resistant Pancreatic Cancer Using a Glycan Biomarker, sTRA.
No full textPURPOSE: A subset of pancreatic ductal adenocarcinomas (PDACs) is highly resistant to systemic chemotherapy, but no markers are available in clinical settings to identify this subset. We hypothesized that a glycan biomarker for PDACs called sialylated tumor-related antigen (sTRA) could be used for this purpose. EXPERIMENTAL DESIGN: We tested for differences between PDACs classified by glycan expression in multiple systems: sets of cell lines, organoids, and isogenic cell lines; primary tumors; and blood plasma from human subjects. RESULTS: The sTRA-expressing models tended to have stem-like gene expression and the capacity for mesenchymal differentiation, in contrast to the nonexpressing models. The sTRA cell lines also had significantly increased resistance to seven different chemotherapeutics commonly used against pancreatic cancer. Patients with primary tumors that were positive for a gene expression classifier for sTRA received no statistically significant benefit from adjuvant chemotherapy, in contrast to those negative for the signature. In another cohort, based on direct measurements of sTRA in tissue microarrays, the patients who were high in sTRA again had no statistically significant benefit from adjuvant chemotherapy. Furthermore, a blood plasma test for the sTRA glycan identified the PDACs that showed rapid relapse following neoadjuvant chemotherapy. CONCLUSIONS: This research demonstrates that a glycan biomarker could have value to detect chemotherapy-resistant PDAC in clinical settings. This capability could aid in the development of stratified treatment plans and facilitate biomarker-guided trials targeting resistant PDAC
A plasmid locus associated with Klebsiella clinical infections encodes a microbiome-dependent gut fitness factor.
Get PDFKlebsiella pneumoniae (Kp) is an important cause of healthcare-associated infections, which increases patient morbidity, mortality, and hospitalization costs. Gut colonization by Kp is consistently associated with subsequent Kp disease, and patients are predominantly infected with their colonizing strain. Our previous comparative genomics study, between disease-causing and asymptomatically colonizing Kp isolates, identified a plasmid-encoded tellurite (TeO3-2)-resistance (ter) operon as strongly associated with infection. However, TeO3-2 is extremely rare and toxic to humans. Thus, we used a multidisciplinary approach to determine the biological link between ter and Kp infection. First, we used a genomic and bioinformatic approach to extensively characterize Kp plasmids encoding the ter locus. These plasmids displayed substantial variation in plasmid incompatibility type and gene content. Moreover, the ter operon was genetically independent of other plasmid-encoded virulence and antibiotic resistance loci, both in our original patient cohort and in a large set (n = 88) of publicly available ter operon-encoding Kp plasmids, indicating that the ter operon is likely playing a direct, but yet undescribed role in Kp disease. Next, we employed multiple mouse models of infection and colonization to show that 1) the ter operon is dispensable during bacteremia, 2) the ter operon enhances fitness in the gut, 3) this phenotype is dependent on the colony of origin of mice, and 4) antibiotic disruption of the gut microbiota eliminates the requirement for ter. Furthermore, using 16S rRNA gene sequencing, we show that the ter operon enhances Kp fitness in the gut in the presence of specific indigenous microbiota, including those predicted to produce short chain fatty acids. Finally, administration of exogenous short-chain fatty acids in our mouse model of colonization was sufficient to reduce fitness of a ter mutant. These findings indicate that the ter operon, strongly associated with human infection, encodes factors that resist stress induced by the indigenous gut microbiota during colonization. This work represents a substantial advancement in our molecular understanding of Kp pathogenesis and gut colonization, directly relevant to Kp disease in healthcare settings
Impact of preoperative antibiotics and other variables on integrated microbiome-host transcriptomic data generated from colorectal cancer resections.
Get PDFBACKGROUND: Integrative multi-omic approaches have been increasingly applied to discovery and functional studies of complex human diseases. Short-term preoperative antibiotics have been adopted to reduce site infections in colorectal cancer (CRC) resections. We hypothesize that the antibiotics will impact analysis of multi-omic datasets generated from resection samples to investigate biological CRC risk factors. AIM: To assess the impact of preoperative antibiotics and other variables on integrated microbiome and human transcriptomic data generated from archived CRC resection samples. METHODS: Genomic DNA (gDNA) and RNA were extracted from prospectively collected 51 pairs of frozen sporadic CRC tumor and adjacent non-tumor mucosal samples from 50 CRC patients archived at a single medical center from 2010-2020. The 16S rRNA gene sequencing (V3V4 region, paired end, 300 bp) and confirmatory quantitative polymerase chain reaction (qPCR) assays were conducted on gDNA. RNA sequencing (IPE, 125 bp) was performed on parallel tumor and non-tumor RNA samples with RNA Integrity Numbers scores ≥ 6. RESULTS: PERMANOVA detected significant effects of tumor vs nontumor histology (P = 0.002) and antibiotics (P = 0.001) on microbial β-diversity, but CRC tumor location (left vs right), diabetes mellitus vs not diabetic and Black/African Ancestry (AA) vs not Black/AA, did not reach significance. Linear mixed models detected significant tumor vs nontumor histology*antibiotics interaction terms for 14 genus level taxa. QPCR confirmed increased Fusobacterium abundance in tumor vs nontumor groups, and detected significantly reduced bacterial load in the (+)antibiotics group. Principal coordinate analysis of the transcriptomic data showed a clear separation between tumor and nontumor samples. Differentially expressed genes obtained from separate analyses of tumor and nontumor samples, are presented for the antibiotics, CRC location, diabetes and Black/AA race groups. CONCLUSION: Recent adoption of additional preoperative antibiotics as standard of care, has a measurable impact on -omics analysis of resected specimens. This study still confirmed increased Fusobacterium nucleatum in tumor
Enhancing the Efficacy of Glutamine Metabolism Inhibitors in Cancer Therapy.
No full textGlutamine metabolism is reprogrammed during tumorigenesis and has been investigated as a promising target for cancer therapy. However, efforts to drug this process are confounded by the intrinsic metabolic heterogeneity and flexibility of tumors, as well as the risk of adverse effects on the anticancer immune response. Recent research has yielded important insights into the mechanisms that determine the tumor and the host immune responses to pharmacological perturbation of glutamine metabolism. Here, we discuss these findings and suggest that, collectively, they point toward patient stratification and drug combination strategies to maximize the efficacy of glutamine metabolism inhibitors as cancer therapeutics
Single-cell co-expression analysis reveals that transcriptional modules are shared across cell types in the brain.
No full textGene-gene relationships are commonly measured via the co-variation of gene expression across samples, also known as gene co-expression. Because shared expression patterns are thought to reflect shared function, co-expression networks describe functional relationships between genes, including co-regulation. However, the heterogeneity of cell types in bulk RNA-seq samples creates connections in co-expression networks that potentially obscure co-regulatory modules. The brain initiative cell census network (BICCN) single-cell RNA sequencing (scRNA-seq) datasets provide an unparalleled opportunity to understand how gene-gene relationships shape cell identity. Comparison of the BICCN data (500,000 cells/nuclei across 7 BICCN datasets) with that of bulk RNA-seq networks (2,000 mouse brain samples across 52 studies) reveals a consistent topology reflecting a shared co-regulatory signal. Differential signals between broad cell classes persist in driving variation at finer levels, indicating that convergent regulatory processes affect cell phenotype at multiple scales
The genetic landscape of metaplastic breast cancers and uterine carcinosarcomas.
Get PDFMetaplastic breast carcinoma (MBC) and uterine carcinosarcoma (UCS) are rare aggressive cancers, characterized by an admixture of adenocarcinoma and areas displaying mesenchymal/sarcomatoid differentiation. We sought to define whether MBCs and UCSs harbor similar patterns of genetic alterations, and whether the different histologic components of MBCs and UCSs are clonally related. Whole-exome sequencing (WES) data from MBCs (n = 35) and UCSs (n = 57, The Cancer Genome Atlas) were reanalyzed to define somatic genetic alterations, altered signaling pathways, mutational signatures, and genomic features of homologous recombination DNA repair deficiency (HRD). In addition, the carcinomatous and sarcomatous components of an additional cohort of MBCs (n = 11) and UCSs (n = 6) were microdissected separately and subjected to WES, and their clonal relatedness was assessed. MBCs and UCSs harbored recurrent genetic alterations affecting TP53, PIK3CA, and PTEN, similar patterns of gene copy number alterations, and an enrichment in alterations affecting the epithelial-to-mesenchymal transition (EMT)-related Wnt and Notch signaling pathways. Differences were observed, however, including a significantly higher prevalence of FAT3 and FAT1 somatic mutations in MBCs compared to UCSs, and conversely, UCSs significantly more frequently harbored somatic mutations affecting FBXW7 and PPP2R1A as well as HER2 amplification than MBCs. Genomic features of HRD and biallelic alterations affecting bona fide HRD-related genes were found to be more prevalent in MBCs than in UCSs. The distinct histologic components of MBCs and UCSs were clonally related in all cases, with the sarcoma component likely stemming from a minor subclone of the carcinoma component in the samples with interpretable chronology of clonal evolution. Despite the similar histologic features and pathways affected by genetic alterations, UCSs differ from MBCs on the basis of FBXW7 and PPP2R1A mutations, HER2 amplification, and lack of HRD, supporting the notion that these entities are more than mere phenocopies of the same tumor type in different anatomical sites