Campos, R. M. | Search bioRxiv

bioRxiv2021

SNAI2-mediated direct repression of BIM protects rhabdomyosarcoma from ionizing radiation

Ionizing radiation (IR) and chemotherapy are the mainstays of treatment for patients with rhabdomyosarcoma (RMS). Yet, the molecular mechanisms that underlie the success or failure of radiotherapy remain unclear. The transcriptional repressor SNAI2 was previously identified as a key regulator of IR sensitivity in normal and malignant stem cells through its repression of the proapoptotic BH3-only gene PUMA. Here, we demonstrate a clear correlation between SNAI2 expression levels and radiosensitivity across multiple RMS cell lines. Moreover, modulating SNAI2 levels in RMS cells through its overexpression or knockdown can alter radiosensitivity in vitro and in vivo. SNAI2 expression reliably promotes overall cell growth and inhibits mitochondrial apoptosis following exposure to IR, with either variable or minimal effects on differentiation and senescence, respectively. Importantly, SNAI2 knockdown results in a striking increase in expression of the proapoptotic BH3-only gene BIM, and ChIP-seq experiments establish that SNAI2 is a direct repressor of BIM. Since the P53 pathway is nonfunctional in the RMS cells used in this study, we have identified a new, P53-independent SNAI2/BIM axis that could potentially predict clinical responses to IR treatment and be exploited to improve RMS therapy. HighlightsO_LISNAI2 expression levels are directly correlated with protection from radiation in rhabdomyosarcoma. C_LIO_LILoss of SNAI2 primes rhabdomyosarcomas for IR-induced apoptosis. C_LIO_LISNAI2 directly represses the expression of the proapoptotic BH3-only gene BIM. C_LI

cancer biology↗

bioRxiv2020

Efficient assessment of nocturnal flying insect communities by combining automatic light traps and DNA metabarcoding

O_LIIncreasing evidence for global insect declines is prompting a renewed interest in the survey of whole insect communities. DNA metabarcoding can contribute to assessing diverse insect communities over a range of spatial and temporal scales, but efforts are still needed to optimise and standardise procedures, from field sampling, through laboratory analysis, to bioinformatic processing. C_LIO_LIHere we describe and test a methodological pipeline for surveying nocturnal flying insects, combining a customised automatic light trap and DNA metabarcoding. We optimised laboratory procedures and then tested the methodological pipeline using 12 field samples collected in northern Portugal in 2017. We focused on Lepidoptera to compare metabarcoding results with those from morphological identification, using three types of bulks produced from each sample (individuals, legs and the unsorted mixture). C_LIO_LIThe customised trap was highly efficient at collecting nocturnal flying insects, allowing a small team to operate several traps per night, and a fast field processing of samples for subsequent metabarcoding with low contamination risks. Morphological processing yielded 871 identifiable individuals of 102 Lepidoptera species. Metabarcoding detected a total of 528 taxa, most of which were Lepidoptera (31.1%), Diptera (26.1%) and Coleoptera (14.7%). There was a reasonably high matching in community composition between morphology and metabarcoding when considering the individuals and legs bulk samples, with few errors mostly associated with morphological misidentification of small microlepidoptera. Regarding the mixture bulk sample, metabarcoding identified nearly four times more Lepidoptera species than morphological examination. C_LIO_LIOur study provides a methodological metabarcoding pipeline that can be used in standardised surveys of nocturnal flying insects, showing that it can overcome limitations and potential shortcomings of traditional methods based on morphological identification. Our approach efficiently collects highly diverse taxonomic groups such as nocturnal Lepidoptera that are poorly represented when using Malaise traps and other widely used field methods. To enhance the potential of this pipeline in ecological studies, efforts are needed to test its effectiveness and potential biases across habitat types and to extend the DNA barcode databases for important groups such as Diptera. C_LI

molecular biology↗