5. Proteomics Investigation of Diverse Serological Patterns in COVID-19 [Molecular & Cellular Proteomics] (First, 20230105)
Our body relies heavily on the secretion of serum antibodies to defend against SARS-CoV-2 attacks. From current clinical reports, we noticed patients with unexpected serological patterns, such as negative antibody expression throughout COVID-19, and exceptionally high expression of IgM or IgG at their plateau. These observations suggest diverse host responses during COVID-19, which have yet to be assessed.
In this study, we applied two-year clinical manifestation and lop、ngitudinal serum proteomics to understand the serology in a cohort of 144 COVID-19 patients. The findings suggest that COVID-19 patients who do not express antibodies developed cellular immunity for viral defense, and that high titers of IgM might not be favorable to COVID-19 recovery.
I contributed to proteomic experiments, data analyses, and manuscript writing.
4. A Common Mechanism of Temperature-sensing in ThermoTRP Channels [Under review] (Co-first, 20220524)
Detecting temperature is crucial for the survival of living organisms. Thermo transient receptor potential (thermoTRP) channels, such as TRPV1 or TRPM8, have been identified as prototypic heat or cold sensors, respectively. However, how they detect temperature remains elusive.
We developed hydroxyl radical footprinting-data-independent acquisition mass spectroscopy (HRF-DIA-MS), a combinative technology, to quantitatively profile the protein residues that undergo burial/exposure conformational rearrangements during temperature activation. Our findings established that the water-protein interaction is a common mechanism underlying temperature sensing in TRPM8 and TRPV1.
I contributed to the proteomic methodology and data analysis.
3. Pulmonary and Renal Long COVID at Two-year Revisit [Under review] (Co-first, 20220419)
More than 450 million individuals have recovered from COVID-19, but little is known about the host responses to long COVID.
We integrated a multi-omics resource containing proteomic and metabolomic analyses of 991 blood and urine specimens from 144 COVID-19 patients. Our data depicts the longitudinal clinical and molecular landscape of COVID-19 with up to two-year follow-up and presents a method to predict pulmonary and renal long COVID.
I contributed to multi-omics experiments, data analyses, and manuscript writing.
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2. Computational Optimization of Spectral Library Size Improves DIA-MS Proteome Coverage and Applications to 15 Tumors [Journal of Proteome Research] (Co-first, 20211108)
Public MS data repositories are being generated for proteomic studies. They provide accessible spectral information for library-based DIA-MS data analyses. However, vast number of false positives may be introduced due to an enlarged search space, leading to an unpleasant proteomic identification.
Via a two-step strategy called subLib to generate experiment-specific subset libraries from the public data, we downscaled the library size while enhanced the resultant proteomic coverages from DIA-MS data by 30-40%. This method is proven handy in proteomics of 15 tumor tissues.
I contributed to data revision and manuscript writing.
1. Proteomic and Metabolomic Investigation of Serum Lactate Dehydrogenase Elevation in COVID-19 Patients [Proteomics] (Co-first, 20210513)
Top Cited Article 2021-2022 in Proteomics
With many risk factors proposed for COVID-19, biological understandings of their mechanisms are in lack. We extracted the published proteomic and metabolomic data to investigate the abnormal elevation of lactate dehydrogenase (LDH), a recognized molecular risk factor in COVID-19 patients. Not only is LDH expression levels associated with COVID-19 severity, its dysregulation associates with organ injuries and hypoxia responses.
The ideas and methods applied in this study could be of reference to other risk factor studies for a more credible medical determinization.
I contributed to data analyses, interpretation, and manuscript writing.