Reliable identification of protein-protein interactions by crosslinking mass spectrometry.

Protein-protein interactions govern most cellular pathways and processes, and multiple technologies have emerged to systematically map them. Assessing the error of interaction networks has been a challenge. Crosslinking mass spectrometry is currently widening its scope from structural analyses of purified multi-protein complexes towards systems-wide analyses of protein-protein interactions (PPIs). Using a carefully controlled large-scale analysis of Escherichia coli cell lysate, we demonstrate that false-discovery rates (FDR) for PPIs identified by crosslinking mass spectrometry can be reliably estimated. We present an interaction network comprising 590 PPIs at 1% decoy-based PPI-FDR. The structural information included in this network localises the binding site of the hitherto uncharacterised protein YacL to near the DNA exit tunnel on the RNA polymerase.

Retention time prediction using neural networks increases identifications in crosslinking mass spectrometry.

Crosslinking mass spectrometry has developed into a robust technique that is increasingly used to investigate the interactomes of organelles and cells. However, the incomplete and noisy information in the mass spectra of crosslinked peptides limits the numbers of protein-protein interactions that can be confidently identified. Here, we leverage chromatographic retention time information to aid the identification of crosslinked peptides from mass spectra. Our Siamese machine learning model xiRT achieves highly accurate retention time predictions of crosslinked peptides in a multi-dimensional separation of crosslinked E. coli lysate. Importantly, supplementing the search engine score with retention time features leads to a substantial increase in protein-protein interactions without affecting confidence. This approach is not limited to cell lysates and multi-dimensional separation but also improves considerably the analysis of crosslinked multiprotein complexes with a single chromatographic dimension. Retention times are a powerful complement to mass spectrometric information to increase the sensitivity of crosslinking mass spectrometry analyses.

Urinary and plasma gonadotropin concentrations in golden lion tamarins (Leontopithecus r. rosalia).

This paper describes the development and validation of a plasma and urinary gonadotropin immunoassay for golden lion tamarins (Leontopithecus rosalia), an endangered New World callitrichid primate. The assay is derived from a macaque chorionic gonadotropin assay and was validated for both plasma and urine samples in L. rosalia. Levels of immunoreactive LH/CG in lion tamarin urine were highly correlated (r = + 0.98) with gonadotropin bioactivity. Immunoreactive LH/CG levels were examined in two contexts: in the urine of adult females and in the plasma of adult males after administration of estrogen. Peaks of gonadotropin excretion were detected in samples collected from nonpregnant adult females. The peaks occurred immediately prior to cyclic elevations in urinary estrogen excretion. Plasma LH/CG concentration in males measured 24 and 48 hours after a single 50 µg injection of estradiol benzoate were significantly lower than levels at these time points measured after control treatment. Together, the results of this study point to the utility of the gonadotropin assay for monitoring reproductive function in both female and male lion tamarins.