Cellular population dynamics shape the route to human pluripotency.

Human cellular reprogramming to induced pluripotency is still an inefficient process, which has hindered studying the role of critical intermediate stages. Here we take advantage of high efficiency reprogramming in microfluidics and temporal multi-omics to identify and resolve distinct sub-populations and their interactions. We perform secretome analysis and single-cell transcriptomics to show functional extrinsic pathways of protein communication between reprogramming sub-populations and the re-shaping of a permissive extracellular environment. We pinpoint the HGF/MET/STAT3 axis as a potent enhancer of reprogramming, which acts via HGF accumulation within the confined system of microfluidics, and in conventional dishes needs to be supplied exogenously to enhance efficiency. Our data suggest that human cellular reprogramming is a transcription factor-driven process that it is deeply dependent on extracellular context and cell population determinants.

Improved SARS-CoV-2 sequencing surveillance allows the identification of new variants and signatures in infected patients.

BACKGROUND: Genomic surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the only approach to rapidly monitor and tackle emerging variants of concern (VOC) of the COVID-19 pandemic. Such scrutiny is crucial to limit the spread of VOC that might escape the immune protection conferred by vaccination strategies or previous virus exposure. It is also becoming clear now that efficient genomic surveillance would require monitoring of the host gene expression to identify prognostic biomarkers of treatment efficacy and disease progression. Here we propose an integrative workflow to both generate thousands of SARS-CoV-2 genome sequences per week and analyze host gene expression upon infection. METHODS: In this study we applied an integrated workflow for RNA extracted from nasal swabs to obtain in parallel the full genome of SARS-CoV-2 and transcriptome of host respiratory epithelium. The RNA extracted from each sample was reverse transcribed and the viral genome was specifically enriched through an amplicon-based approach. The very same RNA was then used for patient transcriptome analysis. Samples were collected in the Campania region, Italy, for viral genome sequencing. Patient transcriptome analysis was performed on about 700 samples divided into two cohorts of patients, depending on the viral variant detected (B.1 or delta). RESULTS: We sequenced over 20,000 viral genomes since the beginning of the pandemic, producing the highest number of sequences in Italy. We thus reconstructed the pandemic dynamics in the regional territory from March 2020 to December 2021. In addition, we have matured and applied novel proof-of-principle approaches to prioritize possible gain-of-function mutations by leveraging patients' metadata and isolated patient-specific signatures of SARS-CoV-2 infection. This allowed us to (i) identify three new viral variants that specifically originated in the Campania region, (ii) map SARS-CoV-2 intrahost variability during long-term infections and in one case identify an increase in the number of mutations in the viral genome, and (iii) identify host gene expression signatures correlated with viral load in upper respiratory ways. CONCLUSION: In conclusion, we have successfully generated an optimized and cost-effective strategy to monitor SARS-CoV-2 genetic variability, without the need of automation. Thus, our approach is suitable for any lab with a benchtop sequencer and a limited budget, allowing an integrated genomic surveillance on premises. Finally, we have also identified a gene expression signature defining SARS-CoV-2 infection in real-world patients' upper respiratory ways.