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Biology subjects

Tang, L. C.

Publications and source records attributed to Tang, L. C..

3 recordsLinked to original sources

De novo gene synthesis by an antiviral reverse transcriptase

Bacteria defend themselves from viral infection using diverse immune systems, many of which sense and target foreign nucleic acids. Defense-associated reverse transcriptase (DRT) systems provide an intriguing counterpoint to this immune strategy by instead leveraging DNA synthesis, but the identities and functions of their DNA products remain largely unknown. Here we show that DRT2 systems execute an unprecedented immunity mechanism that involves de novo gene synthesis via rolling-circle reverse transcription of a non-coding RNA (ncRNA). Unbiased profiling of RT-associated RNA and DNA ligands in DRT2-expressing cells revealed that reverse transcription generates concatenated cDNA repeats through programmed template jumping on the ncRNA. The presence of phage then triggers second-strand cDNA synthesis, leading to the production of long double-stranded DNA. Remarkably, this DNA product is efficiently transcribed, generating messenger RNAs that encode a stop codon-less, never-ending ORF (neo) whose translation causes potent growth arrest. Phylogenetic analyses and screening of diverse DRT2 homologs further revealed broad conservation of rolling-circle reverse transcription and Neo protein function. Our work highlights an elegant expansion of genome coding potential through RNA-templated gene creation, and challenges conventional paradigms of genetic information encoded along the one-dimensional axis of genomic DNA. One-Sentence SummaryBacterial reverse transcriptases synthesize extrachromosomal genes via rolling-circle amplification to confer potent antiviral immunity.

molecular biology↗

A high-throughput approach reveals distinct peptide charging behaviors in electrospray ionization mass spectrometry

Electrospray ionization is a powerful and prevalent technique used to ionize analytes in mass spectrometry. The distribution of charges that an analyte receives (charge state distribution, CSD) is an important consideration for interpreting mass spectra. However, due to an incomplete understanding of the ionization mechanism, the analyte properties that influence CSDs are not fully understood. Here, we employ a machine learning-based high-throughput approach and analyze CSDs of hundreds of thousands of peptides. Interestingly, half of the peptides exhibit charges that differ from what one would naively expect (number of basic sites). We find that these peptides can be classified into two regimes--undercharging and overcharging--and that these two regimes display markedly different charging characteristics. Strikingly, peptides in the overcharging regime show minimal dependence on basic site count, and more generally, the two regimes exhibit distinct sequence determinants. These findings highlight the rich ionization behavior of peptides and the potential of CSDs for enhancing peptide identification.

systems biology↗

SEC-TMT facilitates quantitative differential analysis of protein interaction networks

A proteins molecular interactions and post-translational modifications (PTMs), such as phosphorylation, can be co-dependent and reciprocally co-regulate each other. Although this interplay is central for many biological processes, a systematic method to simultaneously study assembly-states and PTMs from the same sample is critically missing. Here, we introduce SEC-MX (Size Exclusion Chromatography fractions MultipleXed), a global quantitative method combining Size Exclusion Chromatography and PTM-enrichment for simultaneous characterization of PTMs and assembly-states. SEC-MX enhances throughput, allows phosphopeptide enrichment, and facilitates quantitative differential comparisons between biological conditions. Applying SEC-MX to HEK293 and HCT116 cells, we generated a proof-of-concept dataset mapping thousands of phosphopeptides and their assembly-states. Our analysis revealed intricate relationships between phosphorylation events and assembly-states and generated testable hypotheses for follow-up studies. Overall, we establish SEC-MX as a valuable tool for exploring protein functions and regulation beyond abundance changes.

molecular biology↗