Dispersal history of SARS-CoV-2 in Galicia, Spain.

The dynamics of SARS-CoV-2 transmission are influenced by a variety of factors, including social restrictions and the emergence of distinct variants. In this study, we delve into the origins and dissemination of the Alpha, Delta, and Omicron variants of concern in Galicia, northwest Spain. For this, we leveraged genomic data collected by the EPICOVIGAL Consortium and from the GISAID database, along with mobility information from other Spanish regions and foreign countries. Our analysis indicates that initial introductions during the Alpha phase were predominantly from other Spanish regions and France. However, as the pandemic progressed, introductions from Portugal and the USA became increasingly significant. Notably, Galicia's major coastal cities emerged as critical hubs for viral transmission, highlighting their role in sustaining and spreading the virus. This research emphasizes the critical role of regional connectivity in the spread of SARS-CoV-2 and offers essential insights for enhancing public health strategies and surveillance measures.

Comparative analysis of capture methods for genomic profiling of circulating tumor cells in colorectal cancer.

The genomic profiling of circulating tumor cells (CTCs) in the bloodstream should provide clinically relevant information on therapeutic efficacy and help predict cancer survival. Here, we contrasted the genomic profiles of CTC pools recovered from metastatic colorectal cancer (mCRC) patients using different enrichment strategies (CellSearch, Parsortix, and FACS). Mutations inferred in the CTC pools differed depending on the enrichment strategy and, in all cases, represented a subset of the mutations detected in the matched primary tumor samples. However, the CTC pools from Parsortix, and in part, CellSearch, showed diversity estimates, mutational signatures, and drug-suitability scores remarkably close to those found in matching primary tumor samples. In addition, FACS CTC pools were enriched in apparent sequencing artifacts, leading to much higher genomic diversity estimates. Our results highlight the utility of CTCs to assess the genomic heterogeneity of individual tumors and help clinicians prioritize drugs in mCRC.

Clonality and timing of relapsing colorectal cancer metastasis revealed through whole-genome single-cell sequencing.

Recurrence of tumor cells following local and systemic therapy is a significant hurdle in cancer. Most patients with metastatic colorectal cancer (mCRC) will relapse, despite resection of the metastatic lesions. A better understanding of the evolutionary history of recurrent lesions is required to identify the spatial and temporal patterns of metastatic progression and expose the genetic and evolutionary determinants of therapeutic resistance. With this goal in mind, here we leveraged a unique single-cell whole-genome sequencing dataset from recurrent hepatic lesions of an mCRC patient. Our phylogenetic analysis confirms that the treatment induced a severe demographic bottleneck in the liver metastasis but also that a previously diverged lineage survived this surgery, possibly after migration to a different site in the liver. This lineage evolved very slowly for two years under adjuvant drug therapy and diversified again in a very short period. We identified several non-silent mutations specific to this lineage and inferred a substantial contribution of chemotherapy to the overall, genome-wide mutational burden. All in all, our study suggests that mCRC subclones can migrate locally and evade resection, keep evolving despite rounds of chemotherapy, and re-expand explosively.

Limited genomic reconstruction of SARS-CoV-2 transmission history within local epidemiological clusters.

A detailed understanding of how and when severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission occurs is crucial for designing effective prevention measures. Other than contact tracing, genome sequencing provides information to help infer who infected whom. However, the effectiveness of the genomic approach in this context depends on both (high enough) mutation and (low enough) transmission rates. Today, the level of resolution that we can obtain when describing SARS-CoV-2 outbreaks using just genomic information alone remains unclear. In order to answer this question, we sequenced forty-nine SARS-CoV-2 patient samples from ten local clusters in NW Spain for which partial epidemiological information was available and inferred transmission history using genomic variants. Importantly, we obtained high-quality genomic data, sequencing each sample twice and using unique barcodes to exclude cross-sample contamination. Phylogenetic and cluster analyses showed that consensus genomes were generally sufficient to discriminate among independent transmission clusters. However, levels of intrahost variation were low, which prevented in most cases the unambiguous identification of direct transmission events. After filtering out recurrent variants across clusters, the genomic data were generally compatible with the epidemiological information but did not support specific transmission events over possible alternatives. We estimated the effective transmission bottleneck size to be one to two viral particles for sample pairs whose donor-recipient relationship was likely. Our analyses suggest that intrahost genomic variation in SARS-CoV-2 might be generally limited and that homoplasy and recurrent errors complicate identifying shared intrahost variants. Reliable reconstruction of direct SARS-CoV-2 transmission based solely on genomic data seems hindered by a slow mutation rate, potential convergent events, and technical artifacts. Detailed contact tracing seems essential in most cases to study SARS-CoV-2 transmission at high resolution.

SARS-CoV-2 Evolution and Spike-Specific CD4+ T-Cell Response in Persistent COVID-19 with Severe HIV Immune Suppression.

Intra-host evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been reported in cases with persistent coronavirus disease 2019 (COVID-19). In this study, we describe a severely immunosuppressed individual with HIV-1/SARS-CoV-2 coinfection with a long-term course of SARS-CoV-2 infection. A 28-year-old man was diagnosed with HIV-1 infection (CD4+ count: 3 cells/µL nd 563000 HIV-1 RNA copies/mL) and simultaneous Pneumocystis jirovecii pneumonia, disseminated Mycobacterium avium complex infection and SARS-CoV-2 infection. SARS-CoV-2 real-time reverse transcription polymerase chain reaction positivity from nasopharyngeal samples was prolonged for 15 weeks. SARS-CoV-2 was identified as variant Alpha (PANGO lineage B.1.1.7) with mutation S:E484K. Spike-specific T-cell response was similar to HIV-negative controls although enriched in IL-2, and showed disproportionately increased immunological exhaustion marker levels. Despite persistent SARS-CoV-2 infection, adaptive intra-host SARS-CoV-2 evolution, was not identified. Spike-specific T-cell response protected against a severe COVID-19 outcome and the increased immunological exhaustion marker levels might have favoured SARS-CoV-2 persistence.

OmniSARS2: A Highly Sensitive and Specific RT-qPCR-Based COVID-19 Diagnostic Method Designed to Withstand SARS-CoV-2 Lineage Evolution.

Extensive transmission of SARS-CoV-2 during the COVID-19 pandemic allowed the generation of thousands of mutations within its genome. While several of these become rare, others largely increase in prevalence, potentially jeopardizing the sensitivity of PCR-based diagnostics. Taking advantage of SARS-CoV-2 genomic knowledge, we designed a one-step probe-based multiplex RT-qPCR (OmniSARS2) to simultaneously detect short fragments of the SARS-CoV-2 genome in ORF1ab, E gene and S gene. Comparative genomics of the most common SARS-CoV-2 lineages, other human betacoronavirus and alphacoronavirus, was the basis for this design, targeting both highly conserved regions across SARS-CoV-2 lineages and variable or absent in other Coronaviridae viruses. The highest analytical sensitivity of this method for SARS-CoV-2 detection was 94.2 copies/mL at 95% detection probability (~1 copy per total reaction volume) for the S gene assay, matching the most sensitive available methods. In vitro specificity tests, performed using reference strains, showed no cross-reactivity with other human coronavirus or common pathogens. The method was compared with commercially available methods and detected the virus in clinical samples encompassing different SARS-CoV-2 lineages, including B.1, B.1.1, B.1.177 or B.1.1.7 and rarer lineages. OmniSARS2 revealed a sensitive and specific viral detection method that is less likely to be affected by lineage evolution oligonucleotide-sample mismatch, of relevance to ensure the accuracy of COVID-19 molecular diagnostic methods.