Banu, M. | bioRxiv Science

bioRxiv2021

Re-convolving the compositional landscape of primary and recurrent glioblastoma using single nucleus RNA sequencing

Glioblastoma (GBM) is an aggressive diffusely infiltrating neoplasm that spreads beyond surgical resection margins, where it intermingles with non-neoplastic brain cells. This complex microenvironment harboring infiltrating glioma and non-neoplastic brain cells is the origin of tumor recurrence. Thus, understanding the cellular and molecular features of the glioma microenvironment is therapeutically and prognostically important. We used single-nucleus RNA sequencing (snRNAseq) to determine the cellular composition and transcriptional states in primary and recurrent glioma and identified three compositional tissue-states defined by the observed patterns of cohabitation between neoplastic and non-neoplastic brain cells. These comprise states enriched in A) neurons and non-neoplastic glia, B) reactive astrocytes and inflammatory cells, and C) proliferating tumor cells. The tissue states also showed distinct associations with the different transcriptional states of GBM cells. Spatial transcriptomics revealed that the cell-types/transcriptional-states associated with each tissue state colocalize in space. Tissue states are clinically significant because they correlate with radiographic, histopathologic, and prognostic features. Importantly, we found that our compositionally-defined tissue states are enriched in distinct metabolic pathways. One such pathway is fatty acid biosynthesis, which was enriched in tissue state B - a state enriched in recurrent glioblastoma and associated with shorter overall survival- and composed of astrocyte-like/mesenchymal glioma cells, reactive astrocytes, and monocyte-like myeloid cells. We showed that treating acute slices of GBM with a fatty acid synthesis inhibitor is sufficient to deplete the transcriptional signature of tissue state B. Our findings define a novel compositional approach to analyze glioma-infiltrated tissue which allows us to discover prognostic and targetable features, paving the way to new mechanistic and therapeutic discoveries.

pathology↗

bioRxiv2021

Systematic evaluation of genome-wide metabolic landscapes in lactic acid bacteria reveals diet-induced and strain-specific probiotic idiosyncrasies

Lactic acid bacteria (LAB) naturally occur in animal and plant niches and are well-known to elicit several health benefits in humans. Yet, how they adapt their functional metabolic landscapes to diverse nutrient environments and synthesize relevant bioactive compounds remain unexplored across genera, species and strains. Hence, presented herein is a systematic framework for comprehensively characterizing the genome-wide metabolisms of six representative LAB by combining multi-omics data with in silico modeling. We analyse the differences in their growth and cellular fitness, biosynthetic capability of health-relevant compounds, i.e., postbiotics, and probable interactions with 15 common gut microbiota under 11 virtual dietary regimes, and show such attributes are diet- and species-specific. Particularly, some LAB exhibit a desirable balance between synthesis of beneficial postbiotic compounds, positive interactions with beneficial gut commensals, and the ability to colonize and persist in gut environment. We also observe that "high fat-low carb" diets likely lead to detrimental outcomes in most LAB. Our results clearly highlight that probiotics are not "one size fits all" commodities and need to be formulated in a personalised manner for their use as dietary supplements and live biotherapeutics. Overall, the proposed framework will systematize the probiotic administration and could also widen the strain repertoire.

systems biology↗