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Cell Papers Explore Koala Genome Retrovirus Responses, Liver Cancer Proteomics, More

Researchers from China, the US, and Australia describe antisense Piwi-interacting RNA (piRNA) responses to endogenous retroviruses such as KoRV-A in the koala genome. The team performed RNA and piRNA sequencing on testis, liver, and brain samples from two KoRV-A-infected koalas from the wild, analyzing the sequences alongside the koala reference genome and available data for two more koalas. Based on these expression profiles, the authors suggest that KoRV-A is one of at least four endogenous retroviruses that are active in the koala genome, while unspliced versions of the resulting transcripts prompt piRNA processing that may offer some genome protection from the retroviruses. "We speculate that bypassed splicing generates a conserved molecular pattern that directs proviral genomic transcripts to the piRNA biogenesis machinery and that this 'innate' piRNA response suppresses transposition until antisense piRNAs are produced," they suggest, "establishing sequence-specific adaptive immunity."

A team from China and the US take a look at proteomic patterns in a form of hepatocellular carcinoma (HCC) involving hepatitis B infection (HBV). The researchers relied on exome sequencing and isobaric tandem mass tag-based proteomic and phosphoproteomic profiling to assess paired tumor and nearby normal liver tissues from 159 Chinese individuals with HBV-positive HCC, identifying three proteomics-based tumor sub-groups that coincided with other molecular and clinical features, including patient survival in some cases. The proteomic data also offered a broader look at the signaling and metabolic pathways that are active in HCC, the authors explain, noting that the work "provides a valuable resource that significantly expands the knowledge of HBV-related HCC and may eventually benefit clinical practice."

Finally, researchers from the Netherlands share a strategy for sorting cell types using a combination of single-cell RNA sequencing and fluorescence-activated cell sorting data based on cellular properties rather than known cell type markers. The antibody- and cell marker-free method hinges on a computational approach called GateID that "relies on general cellular properties, such as, but not restricted to, cell refractive index, granularity, nuclear staining, cellular proliferation, and mitochondrial activity," the authors explain. By applying GateID to collections of cells from the human pancreas and zebrafish kidney marrow, for example, they successfully teased out and enriched for a range of pancreatic and hematopoietic cell types, respectively.