Biology subjects

McDowell, I.

Publications and source records attributed to McDowell, I..

3 recordsLinked to original sources

bioRxiv2025

Cell type specific analysis of ALS associated proteins reveals immune-regulated targets

A substantial fraction of amyotrophic lateral sclerosis (ALS)-associated proteins remain poorly characterized, in part because of the limited availability of validated research antibodies. We established knockout (KO)-based antibody characterization workflows and demonstrated that widely used antibodies against the major ALS-associated protein C9orf72 lacked specificity (Laflamme et al., 2019). We subsequently scaled this framework to systematically benchmark research antibodies, revealing that up to 61% fail to perform as recommended by manufacturers (Ayoubi et al., 2023). Here, we extend this approach by establishing the ALS-Reproducible Antibody Platform (ALS-RAP), a comprehensive effort to generate a publicly available dataset of KO-validated antibodies targeting proteins encoded by ALS risk genes. In total, we characterized 303 antibodies against 33 ALS-associated proteins to identify high-quality reagents for use in western blot, immunoprecipitation, and immunofluorescence. Using these antibodies, we profiled protein levels across human induced pluripotent stem cell (iPSC)-derived and primary neurological cell types. These analyses revealed diverse cellular distributions and higher levels of several ALS-associated proteins in glial populations, consistent with emerging evidence for immune contributions to ALS. Together, ALS-RAP provides a validated antibody toolbox and protein expression resource to support the study of ALS-associated proteins.

neuroscience↗

bioRxiv2025

Machine Learning-Driven Optimization of Specific, Compact, and Efficient Base Editors via Single-Round Diversification

Base editing shows great potential in research and clinical applications. Current iterations of the deaminases used to create precise single-nucleotide changes via base editing exhibit undesirable effects, including off-targeting, off-base editing, and bystander editing. Current deaminases are derived from either larger eukaryotic deaminases, which exhibit high levels of Cas-independent DNA targeting, or from evolved variants of the smaller E. coli TadA protein (ecTadA), which exhibits off-base editing. To overcome the limitations inherent to using a single protein sequence for engineering, we diversified newly identified TadA orthologs by DNA shuffling to yield millions of training sequences for measuring base editor efficiency. We trained generative models on the performance data from the pools of variants and drew on information-theoretic insights to efficiently explore the sequence space to generate diverse and high-performing deaminases. From a single round of diversification, we created a small set of novel and specific cytosine and adenosine deaminases that were markedly distinct in sequence from published base editor deaminases. We found that our model created deaminases generally outperform those we identified through typical directed evolution. The novel compact deaminases identified here show high on-base activity, comparable to the leading published base editors, and with demonstrably lower off-base activity. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=89 SRC="FIGDIR/small/666807v2_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@cd25c1org.highwire.dtl.DTLVardef@69ad98org.highwire.dtl.DTLVardef@412e4org.highwire.dtl.DTLVardef@1744100_HPS_FORMAT_FIGEXP M_FIG Graphical Abstract C_FIG

bioengineering↗

bioRxiv2023

Assessing the performance of commercial reagent antibodies

Antibodies are critical reagents to detect and characterize proteins. It is commonly understood that many commercial antibodies do not recognize their intended targets, but information on the scope of the problem remains largely anecdotal, and as such, feasibility of the goal of at least one potent and specific antibody targeting each protein in a proteome cannot be assessed. Focusing on antibodies for human proteins, we have scaled a standardized characterization approach using parental and knockout cell lines (Laflamme et al., 2019) to assess the performance of 614 commercial antibodies for 65 neuroscience-related proteins. Side-by-side comparisons of all antibodies against each target, obtained from multiple commercial partners, demonstrates that: i) more than 50% of all antibodies failed in one or more tests, ii) yet, [~]50-75% of the protein set was covered by at least one high-performing antibody, depending on application, suggesting that coverage of human proteins by commercial antibodies is significant; and iii) recombinant antibodies performed better than monoclonal or polyclonal antibodies. The hundreds of underperforming antibodies identified in this study were found to have been used in a large number of published articles, which should raise alarm. Encouragingly, more than half of the underperforming commercial antibodies were reassessed by the manufacturers, and many had alterations to their recommended usage or were removed from the market. This first such study helps demonstrate the scale of the antibody specificity problem but also suggests an efficient strategy toward achieving coverage of the human proteome; mine the existing commercial antibody repertoire, and use the data to focus new renewable antibody generation efforts.

molecular biology↗