HAL-X: Scalable hierarchical clustering for rapid and tunable single-cell analysis.

Data clustering plays a significant role in biomedical sciences, particularly in single-cell data analysis. Researchers use clustering algorithms to group individual cells into populations that can be evaluated across different levels of disease progression, drug response, and other clinical statuses. In many cases, multiple sets of clusters must be generated to assess varying levels of cluster specificity. For example, there are many subtypes of leukocytes (e.g. T cells), whose individual preponderance and phenotype must be assessed for statistical/functional significance. In this report, we introduce a novel hierarchical density clustering algorithm (HAL-x) that uses supervised linkage methods to build a cluster hierarchy on raw single-cell data. With this new approach, HAL-x can quickly predict multiple sets of labels for immense datasets, achieving a considerable improvement in computational efficiency on large datasets compared to existing methods. We also show that cell clusters generated by HAL-x yield near-perfect F1-scores when classifying different clinical statuses based on single-cell profiles. Our hierarchical density clustering algorithm achieves high accuracy in single cell classification in a scalable, tunable and rapid manner.

Intestinal microbiota signatures of clinical response and immune-related adverse events in melanoma patients treated with anti-PD-1.

Ample evidence indicates that the gut microbiome is a tumor-extrinsic factor associated with antitumor response to anti-programmed cell death protein-1 (PD-1) therapy, but inconsistencies exist between published microbial signatures associated with clinical outcomes. To resolve this, we evaluated a new melanoma cohort, along with four published datasets. Time-to-event analysis showed that baseline microbiota composition was optimally associated with clinical outcome at approximately 1 year after initiation of treatment. Meta-analysis and other bioinformatic analyses of the combined data show that bacteria associated with favorable response are confined within the Actinobacteria phylum and the Lachnospiraceae/Ruminococcaceae families of Firmicutes. Conversely, Gram-negative bacteria were associated with an inflammatory host intestinal gene signature, increased blood neutrophil-to-lymphocyte ratio, and unfavorable outcome. Two microbial signatures, enriched for Lachnospiraceae spp. and Streptococcaceae spp., were associated with favorable and unfavorable clinical response, respectively, and with distinct immune-related adverse effects. Despite between-cohort heterogeneity, optimized all-minus-one supervised learning algorithms trained on batch-corrected microbiome data consistently predicted outcomes to programmed cell death protein-1 therapy in all cohorts. Gut microbial communities (microbiotypes) with nonuniform geographical distribution were associated with favorable and unfavorable outcomes, contributing to discrepancies between cohorts. Our findings shed new light on the complex interaction between the gut microbiome and response to cancer immunotherapy, providing a roadmap for future studies.

Lactobacillus johnsonii N6.2 and Blueberry Phytophenols Affect Lipidome and Gut Microbiota Composition of Rats Under High-Fat Diet.

Obesity is considered a primary contributing factor in the development of many diseases, including cancer, diabetes, and cardiovascular illnesses. Phytochemical-rich foods, associated to healthy gastrointestinal microbiota, have been shown to reduce obesity and associated comorbidities. In the present article, we describe the effects of the probiotic Lactobacillus johnsonii N6.2 and blueberry extracts (BB) on the gut microbiota and lipid profile of rats under a high-fat (HF) or low-calorie (LC) diet. L. johnsonii was found to increase the levels of long chain fatty acids (LCFA) in the serum of all animals under HF diet, while reduced LCFA concentrations were observed in the adipose tissue of animals under HF diet supplemented with BB extracts. All animals under HF diet also showed lower protein levels of SREBP1 and SCAP when treated with L. johnsonii. The gut microbiota diversity, ß-diversity was significantly changed by L. johnsonii in the presence of BB. A significant reduction in α-diversity was observed in the ileum of animals under HF diet supplemented with L. johnsonii and BB, while increased α-diversity was observed in the ilium of animals under LC diet supplemented with L. johnsonii or BB. In summary, L. johnsonii and BB supplementation induced significant changes in gut microbiota diversity and lipid metabolism. The phospholipids pool was the lipidome component directly affected by the interventions. The ileum and colon microbiota showed clear differences depending on the diet and the treatments examined.

PrbP modulates biofilm formation in Liberibacter crescens.

In Liberibacter asiaticus, PrbP is a transcriptional regulatory protein involved in survival and persistence during host infection. Tolfenamic acid was previously found to inhibit interactions between PrbP and the promotor region of rplK, resulting in reduced survival of L. asiaticus in the citrus host. In this study, we performed transcriptome analyses to elucidate the PrbP regulon in L. crescens, as it is phylogenetically the closest related species to L. asiaticus that can be grown in laboratory conditions. Chemical inhibition of PrbP with tolfenamic acid revealed that PrbP is involved in the regulation of diverse cellular processes, including stress response, cell motility, cell cycle and biofilm formation. In vitro DNA binding and bacterial two-hybrid assays also suggested that PrbP is a global regulator of multiple transcription factors (RpoH, VisN, PleD, MucR, MocR and CtrA) at both transcriptional and/or post-transcriptional levels. Sub-lethal concentrations of tolfenamic acid significantly reduced the attachment of L. crescens during biofilm formation and decreased long-term persistence in biofilm structures. Overall, our findings show the importance of PrbP in regulating diverse biological processes through direct and indirect interactions with other transcriptional regulators in L. crescens.

Stem-like CD8 T cells mediate response of adoptive cell immunotherapy against human cancer.

Adoptive T cell therapy (ACT) using ex vivo-expanded autologous tumor-infiltrating lymphocytes (TILs) can mediate complete regression of certain human cancers. The impact of TIL phenotypes on clinical success of TIL-ACT is currently unclear. Using high-dimensional analysis of human ACT products, we identified a memory-progenitor CD39-negative stem-like phenotype (CD39-CD69-) associated with complete cancer regression and TIL persistence and a terminally differentiated CD39-positive state (CD39+CD69+) associated with poor TIL persistence. Most antitumor neoantigen-reactive TILs were found in the differentiated CD39+ state. However, ACT responders retained a pool of CD39- stem-like neoantigen-specific TILs that was lacking in ACT nonresponders. Tumor-reactive stem-like TILs were capable of self-renewal, expansion, persistence, and superior antitumor response in vivo. These data suggest that TIL subsets mediating ACT response are distinct from TIL subsets enriched for antitumor reactivity.