Work Package 1 - Emma Teeling
We have collected biological samples from our focal wild and captive bats and generated transcriptome, telomere, immunological data to explore the age related changes that occur across longer and shorter lived bats. We have collected key samples for developing the cellular assays from bat wing punches and have assessed the cellular resistance across multiple bat species and how this changes with age in response to a myriad of different cellular stressors. We have correlated our results with comparative genomic data being collected in WP3. We are optimising single-cell RNA seq for wild bats in collaboration with WP2. We are providing data for all WPs and integrating our results to ascertain the regulators for downstream functional experiments. Ongoing work includes optimization of all methods and a focus on immunological assays and metagenomics.
Work Package 2 - Linfa Wang
Blood and tissue samples of different age groups from the Singapore bat colony are collected for multi-omics analysis. We have optimised the protocols for single-cell RNAseq from low volume of bloods with ongoing generation of single-cell RNAseq data from different bat species. We also in-house generated a panel of monoclonal antibodies to comprehensively profile all the major immune cell types in blood, which enables us to isolate cell types of interest for further functional or molecular analysis. Multiple bat primary and immortalised cell lines are also established with ongoing studies of various stress responses, compared to those of human and mouse cells in vitro, which will uncover novel bat-specific mechanisms for disease resistance and can be followed by BatWorm and BatMouse validation.
Work Package 3 - Michael Hiller
We acquired samples from over 100 bat species, performed genome sequencing, and optimized our assembly workflows, generating many new reference-quality genomes. Several samples were initially problematic and did not sequence well, but we resolved these issues using a new amplification protocol that we are now applying to the remaining difficult samples. We developed TOGA2 for faster and more accurate comparative gene annotation and orthology inference, providing an important foundation for ongoing comparative genomic analyses. Using TOGA2 data, we analyzed inflammasome genes across bats and other mammals, identifying potential candidates for follow-up functional experiments. In addition, we developed a new method to compute more accurate codon alignments, which will support upcoming genome-wide selection analyses. Ongoing work includes methods to date gene losses on the phylogeny, to detect novel genes, to improve comparative gene-expression analyses, and to identify endogenous retroviral insertions and infer their timing within the evolutionary tree.
Work Package 4 - Bjoern Schumacher
We have investigated how conserved genome stability and longevity regulators might contribute to Bat longevity. For this we have devised a strategy for identifying critical regulators. First, we addressed how the DREAM complex might contribute to the prolonged genome maintenance in bats. We have established that DREAM operates as a conserved master regulator of DNA repair gene expression and thus determines DNA repair capacities. We have employed a DREAM signature DNA repair gene expression to assess the status of DREAM activity in bat transcriptomes. In addition, we have used cell biology methodologies to establish the DNA damage response (DDR) in bat cells in comparison to human and mouse cells. We have established cellular DDR assays and identified bat specific mechanisms. For systematically identifying genetic traits of bat longevity, we have devised a complementary strategy for identifying conserved regulators that may have bat specific genetic variants. Complementary to the bat worm approach, we have established a cellular assay system to assess the function of bat genes in human cells. We have established a range of cellular assays including metabolic assays that allow ascertaining bat specific outcomes of longevity-associated gene variants.
