Evaluating the Sensitivity of Mycobacterium tuberculosis to Biotin Deprivation Using Regulated Gene Expression

In the search for new drug targets, we evaluated the biotin synthetic pathway of Mycobacterium tuberculosis (Mtb) and constructed an Mtb mutant lacking the biotin biosynthetic enzyme 7,8-diaminopelargonic acid synthase, BioA. In biotin-free synthetic media, ΔbioA did not produce wild-type levels of biotinylated proteins, and therefore did not grow and lost viability. ΔbioA was also unable to establish infection in mice. Conditionally-regulated knockdown strains of Mtb similarly exhibited impaired bacterial growth and viability in vitro and in mice, irrespective of the timing of transcriptional silencing. Biochemical studies further showed that BioA activity has to be reduced by approximately 99% to prevent growth. These studies thus establish that de novo biotin synthesis is essential for Mtb to establish and maintain a chronic infection in a murine model of TB. Moreover, these studies provide an experimental strategy to systematically rank the in vivo value of potential drug targets in Mtb and other pathogens

Ergothioneine Maintains Redox and Bioenergetic Homeostasis Essential for Drug Susceptibility and Virulence of Mycobacterium tuberculosis

The mechanisms by which Mycobacterium tuberculosis (Mtb) maintains metabolic equilibrium to survive during infection and upon exposure to antimycobacterial drugs are poorly characterized. Ergothioneine (EGT) and mycothiol (MSH) are the major redox buffers present in Mtb, but the contribution of EGT to Mtb redox homeostasis and virulence remains unknown. We report that Mtb WhiB3, a 4Fe-4S redox sensor protein, regulates EGT production and maintains bioenergetic homeostasis. We show that central carbon metabolism and lipid precursors regulate EGT production and that EGT modulates drug sensitivity. Notably, EGT and MSH are both essential for redox and bioenergetic homeostasis. Transcriptomic analyses of EGT and MSH mutants indicate overlapping but distinct functions of EGT and MSH. Last, we show that EGT is critical for Mtb survival in both macrophages and mice. This study has uncovered a dynamic balance between Mtb redox and bioenergetic homeostasis, which critically influences Mtb drug susceptibility and pathogenicity

Artificial intelligence-based pathology as a biomarker of sensitivity to atezolizumab–bevacizumab in patients with hepatocellular carcinoma: a multicentre retrospective study

Background Clinical benefits of atezolizumab plus bevacizumab (atezolizumab–bevacizumab) are observed only in a subset of patients with hepatocellular carcinoma and the development of biomarkers is needed to improve therapeutic strategies. The atezolizumab–bevacizumab response signature (ABRS), assessed by molecular biology profiling techniques, has been shown to be associated with progression-free survival after treatment initiation. The primary objective of our study was to develop an artificial intelligence (AI) model able to estimate ABRS expression directly from histological slides, and to evaluate if model predictions were associated with progression-free survival. Methods In this multicentre retrospective study, we developed a model (ABRS-prediction; ABRS-P), which was derived from the previously published clustering-constrained attention multiple instance learning (or CLAM) pipeline. We trained the model fit for regression analysis using a multicentre dataset from The Cancer Genome Atlas (patients treated by surgical resection, n=336). The ABRS-P model was externally validated on two independent series of samples from patients with hepatocellular carcinoma (a surgical resection series, n=225; and a biopsy series, n=157). The predictive value of the model was further tested in a series of biopsy samples from a multicentre cohort of patients with hepatocellular carcinoma treated with atezolizumab–bevacizumab (n=122). All samples in the study were from adults (aged ≥18 years). The validation sets were sampled between Jan 1, 2008, to Jan 1, 2023. For the multicentre validation set, the primary objective was to assess the association of high versus low ABRS-P values, defined relative to cross-validation median split thresholds in the first biopsy series, with progression-free survival after treatment initiation. Additionally, we performed spatial transcriptomics and matched prediction heatmaps with in situ expression profiles. Findings Of the 840 patients sampled, 641 (76%) were male and 199 (24%) were female. Across the development and validation datasets, hepatocellular carcinoma risk factors included alcohol intake, hepatitis B and C virus infections, and non-alcoholic steatohepatitis. Using cross-validation in the development series, the mean Pearson’s correlation between ABRS-P values and ABRS score (mean expression of ABRS genes) was 0·62 (SD 0·09; mean p<0·0001, SD<0·0001). The ABRS-P generalised well on the external validation series (surgical resection series, r=0·60 [95% CI 0·51–0·68], p<0·0001; biopsy series, r=0·53 [0·40–0·63], p<0·0001). In the 122 patients treated with atezolizumab–bevacizumab, those with ABRS-P-high tumours (n=74) showed significantly longer median progression-free survival than those with ABRS-P-low tumours (n=48) after treatment initiation (12 months [95% CI 7–not reached] vs 7 months [4–9]; p=0·014). Spatial transcriptomics showed significantly higher ABRS score, along with upregulation of various other immune effectors, in tumour areas with high ABRS-P values versus areas with low ABRS-P values. Interpretation Our study indicates that AI applied on hepatocellular carcinoma digital slides is able to serve as a biomarker for progression-free survival in patients treated with atezolizumab–bevacizumab. This approach could be used in the development of inexpensive and fast biomarkers for targeted therapies. The combination of AI heatmaps with spatial transcriptomics provides insight on the molecular features associated with predictions. This methodology could be applied to other cancers or diseases and improve understanding of the biological mechanisms that drive responses to treatments

Whole-Genome and Epigenomic Landscapes of Etiologically Distinct Subtypes of Cholangiocarcinoma

Cholangiocarcinoma (CCA) is a hepatobiliary malignancy exhibiting high incidence in countries with endemic liver-fluke infection. We analysed 489 CCAs from 10 countries, combining whole-genome (71 cases), targeted/exome, copy-number, gene expression, and DNA methylation information. Integrative clustering defined four CCA clusters - Fluke-Positive CCAs (Clusters 1/2) are enriched in ERBB2 amplifications and TP53 mutations, conversely Fluke-Negative CCAs (Clusters 3/4) exhibit high copy-number alterations and PD-1/PD-L2 expression, or epigenetic mutations (IDH1/2, BAP1) and FGFR/PRKA-related gene rearrangements. Whole-genome analysis highlighted FGFR2 3'UTR deletion as a mechanism of FGFR2 upregulation. Integration of non-coding promoter mutations with protein-DNA binding profiles demonstrates pervasive modulation of H3K27me3-associated sites in CCA. Clusters 1 and 4 exhibit distinct DNA hypermethylation patterns targeting either CpG islands or shores - mutation signature and subclonality analysis suggests that these reflect different mutational pathways. Our results exemplify how genetics, epigenetics and environmental carcinogens can interplay across different geographies to generate distinct molecular subtypes of cancer