Biology subjects

Lin, C. T.

Publications and source records attributed to Lin, C. T..

3 recordsLinked to original sources

bioRxiv2026

3D, multi-omic imaging reveals molecular biomarkers of the pre-metastatic niche in lung cancer

The recurrence rate following complete surgical resection of primary non-small cell lung cancer is as high as 55%, yet no approach currently exists to evaluate the risk of local recurrence. The premetastatic paradigm is the recognition that metastasis is preceded by reprogramming naive tissues to prime a microenvironment for tumor cell survival and subsequent reactivation. Identification of biomarkers of the pre-metastatic niche would allow us to evaluate a patients risk of local relapse in the normal lung parenchyma surrounding the resected tumor. We designed a workflow incorporating in vivo modelling, radiology, and deep learning-guided three-dimensional (3D) imaging, spatial proteomics, and transcriptomics to identify previously unreported signals associated with the early transformation of the lung parenchyma announcing regional metastasis. We curated biorepository spanning timepoints before and after resection of primary Lewis Lung Carcinoma (LLC) tumors. Using radiology and cellular resolution 3D histology, we calculated the number and distribution of metastases in mouse lungs and developed an algorithm to guide placement of spatial proteomics and transcriptomics to regions containing early micro-metastases and the pre-metastatic microenvironment. Molecular and tissue features associated with presence, size, and location of metastases guided the identification of both myeloid (F4/80) and senescent (p16/p21) cell signatures in the premetastatic and metastatic environments. Finally, multiparametric flow cytometry of metastatic lungs in a senescence reporter GEMM (tdTomato-p16 INKA mice) resolved senescent cells including alveolar macrophages as the cellular phenotypes associated with these early premetastatic signatures. Altogether, this work highlights a novel AI-assisted approach for detection of biomarkers of tissue remodeling during lung cancer invasion.

bioengineering↗

bioRxiv2025

A conserved region T-cell vaccine for Sarbecoviruses

The rapid development of vaccines was a critical part of the global response to the COVID-19 pandemic. SARS-CoV-2 (a Sarbecovirus and member of the Betacoronavirus genus responsible for the pandemic) virus was first detected in Wuhan, China in late 2019. Effective mRNA vaccines based on the viral Spike protein were designed from the earliest isolates and available by December of 2020. SARS-CoV-2 has continued to evolve in the human population, accruing neutralizing antibody resistance mutations that have necessitated updating the vaccine periodically to better match contemporary variants. Neutralizing antibody cross-reactivity is generally very limited among the diverse members of the betacoronavirus genus that are of clinical importance in people. Here, we present an alternative vaccine strategy based on eliciting T-cell responses targeting four highly conserved regions shared across the betacoronavirus proteomes. We hypothesized that cross-reactive responses to these regions could temper disease severity. Focusing immune responses on highly conserved epitopes could be beneficial as SARS-CoV-2 continues to evolve, or if a novel betacoronavirus should enter the human population. Vaccination with these highly conserved regions induced robust T-cell responses in mice and rhesus macaques. Vaccinated hamsters were significantly protected against weight loss and lung inflammation after challenge with the SARS-CoV-2 Omicron variant. After a SARS-CoV-2 Delta challenge in rhesus macaques, 3 out of 4 animals in the control group had infectious virus in their bronchoalveolar lavage samples, while the 4 animals in the vaccinated group did not.

immunology↗

bioRxiv2024

Evolution engineering of methylotrophic E. coli enables faster growth than native methylotrophs

As methanol can be derived from either CO2 or methane, methanol economy may play a role in combating climate change. In this scenario, rapid utilization of methanol by an industrial microorganism is the first and crucial step for efficient utilization of the C1 feedstock chemical. Here, we report the development of a methylotrophic E. coli strain (SM6) with a doubling time of 3.5 hours, outpacing that of common native methylotrophs. We accomplish this using evolution engineering with dynamic copy number variation (CNV). We developed a bacterial artificial chromosome (BAC) with dynamic CNV to facilitate overcoming the formaldehyde-induced DNA-protein cross-linking (DPC) problem in the evolution process. The growth rate of the organism in methanol minimal medium improved significantly after it acquired a loss-of-function mutation in mutS. We tracked the genome variations of 72 cultures along the evolution process by next-generation sequencing, and identified the metabolic features of the fast-growing strain. This study illustrates the potential of dynamic CNV as an evolution tool and synthetic methylotrophs as a platform for sustainable biotechnological applications.

synthetic biology↗