Biology subjects

Mendjan, S.

Publications and source records attributed to Mendjan, S..

5 recordsLinked to original sources

bioRxiv2021

Quantitative accuracy and precision in multiplexed single-cell proteomics.

Single-cell proteomics workflows have considerably improved in sensitivity and reproducibility to characterize yet unknown biological phenomena. With the emergence of multiplexed single-cell proteomics, studies increasingly present single-cell measurements in conjunction with an abundant congruent carrier to improve precursor selection and enhance identifications. While these extreme carrier spikes are often >100-times more abundant than the investigated samples, undoubtedly the total ion current increases, but quantitative accuracy possibly is affected. We here focus on narrowly titrated carrier spikes (i.e., <20x) and assess their elimination for comparable sensitivity at superior accuracy. We find that subtle changes in the carrier ratio can severely impact measurement variability and describe alternative multiplexing strategies to evaluate data quality. Lastly, we demonstrate elevated replicate overlap while preserving acquisition throughput at improved quantitative accuracy with DIA-TMT and discuss optimized experimental designs for multiplexed proteomics of trace samples. This comprehensive benchmarking gives an overview of currently available techniques and guides conceptualizing the optimal single-cell proteomics experiment.

biochemistry↗

bioRxiv2021

ZFP462 targets heterochromatin to transposon-derived enhancers restricting transcription factor binding and expression of lineage-specifying genes

ZNF462 haploinsufficiency is linked to Weiss-Kruszka Syndrome, a genetic disorder characterized by a range of neurodevelopmental defects including Autism. Though it is highly conserved in vertebrates and essential for embryonic development the molecular functions of ZNF462 are unclear. We identified its murine homolog ZFP462 in a screen for epigenetic gene silencing in mouse embryonic stem cells (mESCs). Here, we show ZFP462 safeguards neural lineage specification by targeting the H3K9-specific histone methyltransferase complex G9A/GLP to mediate epigenetic silencing of endodermal genes. ZFP462 binds to thousands of transposable elements (TEs) that harbor ESC- and endoderm-specific transcription factor (TF) binding sites and act as enhancers. Through physical interaction with G9A/GLP, ZFP462 seeds heterochromatin at TE-derived enhancers restricting the binding of core pluripotency TFs OCT4 and SOX2. Loss of ZFP462 in ESCs results in increased chromatin accessibility at target sites and ectopic expression of endodermal genes. Taken together, ZFP462 restricts TF binding and subsequent endodermspecific gene activation by conferring lineage and locus-specificity to the broadly expressed epigenetic regulator G9A/GLP. Our results suggest that aberrant activation of endodermal genes in the neuronal lineage underlies ZNF462-associated neurodevelopmental pathology.

genetics↗

bioRxiv2021

An automated workflow for label-free and multiplexed single cell proteomics sample preparation at unprecedented sensitivity.

The analysis of single-cell proteomes has recently become a viable complement to transcriptomics and genomics studies. Proteins are the primary driver of cellular functionality and mRNA levels are often an unreliable proxy of such. Therefore, the global analysis of the proteome is essential to study cellular identities. Multiplexed and label-free mass spectrometry-based approaches with single-cell resolution have lately attributed surprising heterogeneity to presumed homogenous cell populations. Even though specialized experimental designs and instrumentation have demonstrated remarkable advances, the efficient sample preparation of single cells still lag. Here, we introduce the proteoCHIP, a universal option for single-cell proteomics sample preparation at surprising sensitivity and throughput. The automated processing using a commercial system combining single-cell isolation and picoliter dispensing, the cellenONE(R), reduces final sample volumes to low nanoliters submerged in a hexadecane layer simultaneously eliminating error-prone manual sample handling and overcoming evaporation. The specialized proteoCHIP design allows direct injection of single cells via a standard autosampler resulting in around 1,500 protein groups per analytical run at remarkable reporter ion signal to noise while reducing or eliminating the carrier proteome. We identified close to 2,600 proteins across 170 multiplexed single cells from two highly similar human cell types. This dedicated loss-less workflow allows distinguishing in vitro co-differentiated cell types of self-organizing cardiac organoids based on indicative markers across 150 single cells. In-depth characterization revealed enhanced cellular motility of cardiac endothelial cells and sarcomere organization in cardiomyocytes. Our versatile and automated sample preparation has not only proven to be easily adaptable but is also sufficiently sensitive to drive biological applications of single-cell proteomics.

biochemistry↗

bioRxiv2021

Comparative proteome signatures of ultra-low input samples by TMT multiplexed Data-Independent Acquisition

Single cell transcriptomics has revolutionized our understanding of basic biology and disease. Since transcript levels often do not correlate with protein expression, it is crucial to complement transcriptomics approaches with proteome analyses at single cell resolution. Despite continuous technological improvements in sensitivity, mass spectrometry-based single cell proteomics ultimately faces the challenge of reproducibly comparing the protein expression profiles of thousands of individual cells. Here, we combine two hitherto opposing analytical strategies, DIA and Tandem-Mass-Tag (TMT)-multiplexing, to generate highly reproducible, quantitative proteome signatures from ultra-low input samples. While conventional, data-dependent shotgun proteomics (DDA) of ultra-low input samples critically suffers from the accumulation of missing values with increasing sample-cohort size, data-independent acquisition (DIA) strategies do usually not take full advantage of isotope-encoded sample multiplexing. We developed a novel, identification-independent proteomics data-analysis pipeline that allows to quantitatively compare DIA-TMT proteome signatures across hundreds of samples independent of their biological origin, and to identify cell types and single protein knockouts. We validate our approach using integrative data analysis of different human cell lines and standard database searches for knockouts of defined proteins. These data establish a novel and reproducible approach to markedly expand the numbers of proteins one detects from ultra-low input samples, such as single cells.

biochemistry↗

bioRxiv2020

Cardioids reveal self-organizing principles of human cardiogenesis

Organoids that self-organize into tissue-like structures have transformed our ability to model human development and disease. To date, all major organs can be mimicked using self-organizing organoids with the notable exception of the human heart. Here, we established self-organizing cardioids from human pluripotent stem cells that intrinsically specify, pattern and morph into chamber-like structures containing a cavity. Cardioid complexity can be controlled by signaling that instructs the separation of cardiomyocyte and endothelial layers, and by directing epicardial spreading, inward migration and differentiation. We find that cavity morphogenesis is governed by a mesodermal WNT-BMP signaling axis and requires its target HAND1, a transcription factor linked to human heart chamber cavity defects. In parallel, a WNT-VEGF axis coordinates myocardial self-organization with endothelial patterning and specification. Human cardioids represent a powerful platform to mechanistically dissect self-organization and congenital heart defects, serving as a foundation for future translational research. Highlights- Cardioids form cardiac-like chambers with inner endothelial lining and interact with epicardium - Cardioid self-organization and lineage complexity can be controlled by signaling - WNT-BMP signaling directs cavity formation in self-organized cardioids via HAND1 - WNT-VEGF coordinate endothelial patterning with myocardial cavity morphogenesis

developmental biology↗