Biology subjects

Perlstein, D. L.

Publications and source records attributed to Perlstein, D. L..

3 recordsLinked to original sources

bioRxiv2025

The Cia1 and Cia2 subunits of the CTC mediate recognition of apo-FeS proteins with a C-terminal targeting complex recognition motif

The cytosolic iron-sulfur cluster assembly (CIA) targeting complex is responsible for maturation of cytosolic and nuclear iron-sulfur enzymes, numbering >30 proteins critical for fundamental processes such as DNA replication and repair. Up to 25% of these client proteins terminate in a targeting complex recognition (TCR) motif. This carboxy-terminal tripeptide motif recruits the CIA targeting complex (CTC) to the client so that the metallocluster can be inserted. Herein, we use a combination of computational, biochemical and biophysical approaches to determine that the clients bearing a TCR motif docks at the interface of the Cia1 and Cia2 subunits of the CTC. Thus, mutations destabilizing the Cia1-Cia2 complex also disrupt TCR-based client identification by the CTC. Our study also reveals that the understudied human Cia2 paralog CIAO2A, which is proposed to be a specific targeting factor for iron regulatory protein 1, can recruit clients terminating in the TCR peptide. These data signal that CIAO2A plays a more general role in iron-sulfur protein maturation than previously appreciated. Taken together, our findings deepen our understanding of the molecular basis for client recognition by the CTC that is critical to understand the impact of CIA function in human health and disease.

biochemistry↗

bioRxiv2024

Getting Started with Machine Learning for Experimental Biochemists and Other Molecular Scientists

Machine learning (ML) is rapidly gaining traction in many areas of experimental molecular science for elucidating relationships and patterns in large or complex data sets. Historically, ML was largely the preserve of those with specialized training in fields such as statistics or cheminformatics. Increasingly, however, ML methodologies are becoming part of the standard toolkit for experimental scientists across a range of disciplines. Lowering the barrier of entry to these ML techniques, for scientists without a significant background in computer science or statistics, is important to broadening access to these powerful methods. Here we provide detailed, step by step tutorials for performing four ML methods that are particularly useful for applications in biochemistry, cell biology, and drug discovery: hierarchical clustering, Principal Component Analysis (PCA), Partial Least-Squares Discriminant Analysis (PLSDA), and Partial Least-Squares Regression (PLSR). The protocols are written for the widely used software MATLAB, but no prior experience with MATLAB is required to use them. We include an explanation of each step, pitched at a level to be understood by investigators without any prior experience with ML, MATLAB, or any kind of coding. We also highlight the scientific issues pertaining to selecting and scaling the data to be analyzed, and describe controls to test the validity of the results obtained. Throughout, we emphasize the relationship between the scientific question and how to choose data and methods that will allow it to be addressed in a meaningful way. Our aim is to provide a basic introduction that will equip experimental chemical biologists and other chemical and biomedical scientists with the knowledge required to use ML to aid in the design of experiments, the formulation and data-driven testing of hypotheses, and the analysis of experimental data. Basic Protocol 1Clustering Basic Protocol 2Principal Component Analysis (PCA) Basic Protocol 3Partial Least Squares Discriminant Analysis (PLSDA) Basic Protocol 4Partial Least Squares Regression (PLSR)

biochemistry↗

bioRxiv2023

Cytosolic iron-sulfur protein assembly system identifies clients by a C-terminal tripeptide

The eukaryotic cytosolic Fe-S protein assembly (CIA) machinery inserts iron-sulfur (Fe-S) clusters into cytosolic and nuclear proteins. In the final maturation step, the Fe-S cluster is transferred to the apo-proteins by the CIA-targeting complex (CTC). However, the molecular recognition determinants of client proteins are unknown. We show that a conserved [LIM]-[DES]-[WF]-COO- tripeptide present at the C-terminus of clients is necessary and sufficient for binding to the CTC in vitro and directing Fe-S cluster delivery in vivo. Remarkably, fusion of this TCR (target complex recognition) signal enables engineering of cluster maturation on a non-native protein via recruitment of the CIA machinery. Our study significantly advances our understanding of Fe-S protein maturation and paves the way for bioengineering applications. One-Sentence SummaryA C-terminal tripeptide guides eukaryotic iron-sulfur cluster insertion into cytosolic and nuclear proteins.

biochemistry↗