High-quality MS/MS spectrum prediction for data-dependent and data-independent acquisition data analysis.

Peptide fragmentation spectra are routinely predicted in the interpretation of mass-spectrometry-based proteomics data. However, the generation of fragment ions has not been understood well enough for scientists to estimate fragment ion intensities accurately. Here, we demonstrate that machine learning can predict peptide fragmentation patterns in mass spectrometers with accuracy within the uncertainty of measurement. Moreover, analysis of our models reveals that peptide fragmentation depends on long-range interactions within a peptide sequence. We illustrate the utility of our models by applying them to the analysis of both data-dependent and data-independent acquisition datasets. In the former case, we observe a q-value-dependent increase in the total number of peptide identifications. In the latter case, we confirm that the use of predicted tandem mass spectrometry spectra is nearly equivalent to the use of spectra from experimental libraries.

ELISA detection of SARS-CoV-2 antibodies in saliva.

To facilitate containment of the COVID-19 pandemic currently active in the United States and across the world, options for easy, non-invasive antibody testing are required. Here we have adapted a commercially available, serum-based enzyme-linked immunosorbent assay (ELISA) for use with saliva samples, achieving 84.2% sensitivity and 100% specificity in a set of 149 clinical samples. This strategy will enable widespread, affordable testing for patients who experienced this disease, whilst minimizing exposure risk for healthcare workers.

Determination of ubiquitin fitness landscapes under different chemical stresses in a classroom setting.

Ubiquitin is essential for eukaryotic life and varies in only 3 amino acid positions between yeast and humans. However, recent deep sequencing studies indicate that ubiquitin is highly tolerant to single mutations. We hypothesized that this tolerance would be reduced by chemically induced physiologic perturbations. To test this hypothesis, a class of first year UCSF graduate students employed deep mutational scanning to determine the fitness landscape of all possible single residue mutations in the presence of five different small molecule perturbations. These perturbations uncover 'shared sensitized positions' localized to areas around the hydrophobic patch and the C-terminus. In addition, we identified perturbation specific effects such as a sensitization of His68 in HU and a tolerance to mutation at Lys63 in DTT. Our data show how chemical stresses can reduce buffering effects in the ubiquitin proteasome system. Finally, this study demonstrates the potential of lab-based interdisciplinary graduate curriculum.

Lactate dehydrogenase B is required for the growth of KRAS-dependent lung adenocarcinomas.

PURPOSE: This study is aimed to identify genes within the KRAS genomic amplicon that are both coupregulated and essential for cell proliferation when KRAS is amplified in lung cancer. EXPERIMENTAL DESIGN: We used an integrated genomic approach to identify genes that are coamplified with KRAS in lung adenocarcinomas and subsequently preformed an RNA interference (RNAi) screen to uncover functionally relevant genes. The role of lactate dehydrogenase B (LDHB) was subsequently investigated both in vitro and in vivo by siRNA and short hairpin RNA (shRNA)-mediated knockdown in a panel of lung adenocarcinoma cells lines. LDHB expression was also investigated in patient tumors using microarray and immunohistochemistry analyses. RESULTS: RNAi-mediated depletion of LDHB abrogated cell proliferation both in vitro and in xenografted tumors in vivo. We find that LDHB expression correlates to both KRAS genomic copy number gain and KRAS mutation in lung cancer cell lines and adenocarcinomas. This correlation between LDHB expression and KRAS status is specific for lung cancers and not other tumor types that harbor KRAS mutations. Consistent with a role for LDHB in glycolysis and tumor metabolism, KRAS-mutant lung tumors exhibit elevated expression of a glycolysis gene signature and are more dependent on glycolysis for proliferation compared with KRAS wild-type lung tumors. Finally, high LDHB expression was a significant predictor of shorter survival in patients with lung adenocarcinomas. CONCLUSION: This study identifies LDHB as a regulator of cell proliferation in a subset of lung adenocarcinoma and may provide a novel therapeutic approach for treating lung cancer.