Biology subjects

Strickland, M.

Publications and source records attributed to Strickland, M..

4 recordsLinked to original sources

bioRxiv2023

Ultrasensitive detection of circulating LINE-1 ORF1p as a specific multi-cancer biomarker

Improved biomarkers are needed for early cancer detection, risk stratification, treatment selection, and monitoring treatment response. While proteins can be useful blood-based biomarkers, many have limited sensitivity or specificity for these applications. Long INterspersed Element-1 (LINE-1, L1) open reading frame 1 protein (ORF1p) is a transposable element protein overexpressed in carcinomas and high-risk precursors during carcinogenesis with negligible detectable expression in corresponding normal tissues, suggesting ORF1p could be a highly specific cancer biomarker. To explore the potential of ORF1p as a blood-based biomarker, we engineered ultrasensitive digital immunoassays that detect mid-attomolar (10-17 M) ORF1p concentrations in patient plasma samples across multiple cancers with high specificity. Plasma ORF1p shows promise for early detection of ovarian cancer, improves diagnostic performance in a multi-analyte panel, and provides early therapeutic response monitoring in gastric and esophageal cancers. Together, these observations nominate ORF1p as a multi-cancer biomarker with potential utility for disease detection and monitoring. Statement of SignificanceLINE-1 ORF1p transposon protein is pervasively expressed in many cancers and a highly specific biomarker of multiple common, lethal carcinomas and their high-risk precursors in tissue and blood. Ultrasensitive ORF1p assays from as little as 25 L plasma are novel, rapid, cost-effective tools in cancer detection and monitoring.

cancer biology↗

bioRxiv2022

ApoE isoforms differentially regulate neuronal membrane proteasomes to shift the threshold for pathological aggregation of endogenous Tau

Neuroproteasomes are a subset of 20S proteasomes that are localized to the neuronal plasma membrane and degrade newly synthesized proteins. To date, the molecular composition of neuroproteasomes is undefined, and moreover, whether neuroproteasomes can influence protein aggregation with relevance to neurodegenerative disorders remains unexplored. Using a Cre-dependent conditional knock-in mouse line to endogenously tag the proteasome, we find that neuroproteasomes co-purify with ApoE, the most significant risk factor for late-onset Alzheimers Disease (AD). We discover that neuroproteasome membrane localization is differentially modulated by ApoE isoforms (E4<E3<E2) in vitro, in vivo, and in human postmortem samples. We synthesized selective, neuroproteasome-specific inhibitors and discovered that neuroproteasome inhibition induces aggregation of endogenous mouse and human Tau, without the need for seeding or pathogenic mutations. Using hApoE-KI/hTau-KI crosses, we find that ApoE isoforms differentially shift the aggregation threshold for Tau. Neuroproteasome inhibition in vivo is sufficient to induce sarkosyl-insoluble and Thioflavin-S positive endogenous Tau aggregates in only three days, which are completely abrogated by co-application of cycloheximide. Newly synthesized Tau levels increase threefold after neuroproteasome inhibition, leading us to posit that newly synthesized Tau is uniquely susceptible to aggregation due to neuroproteasome dysfunction. Overall, our data define neuroproteasomes as a pivotal proteostasis mechanism underlying the formation of endogenous Tau aggregates, which is directly regulated by the largest genetic risk factor for late-onset Alzheimers Disease.

neuroscience↗

bioRxiv2020

Structural basis for polyglutamate chain initiation and elongation by TTLL family enzymes

Glutamylation, introduced by TTLL enzymes, is the most abundant modification of brain tubulin. Essential effector proteins read the tubulin glutamylation pattern, and its misregulation causes neurodegeneration. TTLL glutamylases posttranslationally add glutamates to internal glutamates in tubulin C-terminal tails (branch initiation, through an isopeptide bond), and additional glutamates can extend these (elongation). TTLLs are thought to specialize for initiation or elongation, but the mechanistic basis for regioselectivity is unknown. We present cocrystal structures of murine TTLL6 bound to tetrahedral intermediate analogs that delineate key active-site residues that make this an elongase. We show that TTLL4 is exclusively an initiase, and through combined structural and phylogenetic analyses, engineer TTLL6 into a branch-initiating enzyme. TTLL glycylases add glycines posttranslationally to internal glutamates, and we find that the same active-site residues discriminate between initiase and elongase glycylases. These active-site specializations of TTLL glutamylases and glycylases ultimately yield the chemical complexity of cellular microtubules.

biochemistry↗

bioRxiv2017

Computational correction of copy-number effect improves specificity of CRISPR-Cas9 essentiality screens in cancer cells

The CRISPR-Cas9 system has revolutionized gene editing both on single genes and in multiplexed loss-of-function screens, enabling precise genome-scale identification of genes essential to proliferation and survival of cancer cells. However, previous studies reported that an anti-proliferative effect of Cas9-mediated DNA cleavage confounds such measurement of genetic dependency, particularly in the setting of copy number gain1-4. We performed genome-scale CRISPR-Cas9 essentiality screens on 342 cancer cell lines and found that this effect is common to all lines, leading to false positive results when targeting genes in copy number amplified regions. We developed CERES, a computational method to estimate gene dependency levels from CRISPR-Cas9 essentiality screens while accounting for the copy-number-specific effect, as well as variable sgRNA activity. We applied CERES to sets of screens performed with different sgRNA libraries and found that it reduces false positive results and provides meaningful estimates of sgRNA activity. As a result, the application of CERES improves confidence in the interpretation of genetic dependency data from CRISPR-Cas9 essentiality screens of cancer cell lines.

genomics↗