Analysis of expression of PDCP and MAL13P1.308 of Plasmodium falciparum employing a quantitative proteomics approach based on SILAC

Plasmodium falciparum is a deadly parasite that causes malaria in humans. This disease causes the death of one million people every year. To find new means to fight this parasite, it is important to learn more about its biology. As the pathways of protein expression are better understood, it becomes easier to find out how to block these mechanisms. The completion of the genome sequencing has opened new perspective of genome wide analysis. One of these studies was done by LaCount et al. who used the yeast1two1hybrid system to map the complete interaction network between proteins of P. falciparum. ¨ From this network of interaction an interesting protein was studied further by Daubenberger et al. which is PDCP. This protein is closely related to MSP11 in this protein network, a protein involved in erythrocyte invasion. PDCP is a CCCH1type zinc finger protein, a family of proteins that are involved in protein1protein interaction, nucleic acid binding and binding in small ligands. It was shown that its expression was dependant on the density of the parasites. In this study we used the SILAC technology to confirm these previous results. A culture is grown with isotopically heavy isoleucine in the medium as a control sample. After a few cell cycles, almost all the natural isoleucines are replaced with the labeled ones. Three cultures with parasitemia of 2, 5 and 10% are grown and mixed with an equal amount of the control culture. When the proteins are analyzed by mass spectrometry, the peptides that contained isoleucine will be detected as two separate peaks. After normalization of each peptide area with this internal control, the quantity of PDCP can be compared between cultures of different parasitemias. 11 peptides of PDCP have been detected by mass spectrometry, proving its existence for the first time. These peptides were labeled to more than 95%, allowing the comparison of PDCP expression between the cultures. But because of difficulty of reproducibility in in vitro cultures, the regulation of PDCP by the parasitemia has not been observed by SILAC. We wanted to study further the protein interaction network in which PDCP is involved. MAL13P1.308, a protein directly interacting with PDCP and MSP11 in the protein network map, was analyzed by IFA. It was found to be expressed during all stages of the asexual blood stage cycle and it was not imported in the host cell. The next step will be to see if it interacts with PDCP by co1localization studies

Elucidating regulatory mechanisms shaping the transcriptome and proteome of the gut immune response in Drosophila melanogaster

Michael Vincent Frochaux

Work on Drosophila melanogaster paved the way to our current understanding of modern genetics. Since then, this model organism has contributed greatly to various fields such as neurobiology, development, and immunology. The discovery and analysis of the various pathways of the Drosophila immune response led the way to the in-depth characterization of the gut immune response. Furthermore, a genome-wide association study on a population of Drosophila identified resistance to infection by the entomopathogenic bacteria Pseudomonas entomophila (P.e.) as a complex phenotype, with highly resistant and susceptible lines, and highlighted genes and pathways mediating inter-individual differences. However, the molecular mechanisms mediating the resistance to enteric infection remain largely uncharacterized. This study uses the same Drosophila population to analyze what are the molecular mechanisms mediating the resistance to enteric infection. We analyzed the genetic determinants of gene expression variation among the most resistant and susceptible lines in response to infection using expression quantitative trait loci (eQTL) analysis. We also characterized the mode of action of these eQTLs into cis- and trans-acting. Furthermore, we identified the gene nutcracker (ntc) as the only differentially-expressed gene between resistance classes. We then demonstrate that loss of function ntc mutants are significantly more susceptible to infection and then identify a single nucleotide polymorphism (SNP) located in a transcription factor binding site (TFBS) which affects the binding affinity of the transcription factor Broad leading to allele-specific expression variation of the gene ntc. If the transcriptomic response to infection has been thoroughly characterized, it is not the case for the proteomic response. We thus sought to characterize for the first time the proteomic response of the Drosophila to enteric infection. We performed mass spectrometry and RNA sequencing on dissected guts from flies infected by two Gram-negative bacteria, Erwinia carotovora carotovora 15 (Ecc15) or Pseudomonas entomophila, 4h and 16h after infection. We found that a large portion of the measurable proteome (12%) varies after infection and that protein changes are strongly time- and infection-dependent. We showed the relatively poor correlation between gene expression and protein abundance in the Drosophila enteric immune response. Finally, we performed a screen of several proteins that were identified in our proteomics work but had previously not been found when assessing the gene expression response to infection using loss-of-function mutants and identifying 7 genes that modulate overall susceptibility to P.e. infection. In summary, this work analyze the genetic determinants of gene expression variation in the DGRP population upon infection and characterize them according to their mode of action. Furthermore, we describe how a non-coding variant lowers resistance to infection by modulating ntc gene expression through altered Broad repressor binding. Finally, it provides the first comprehensive characterization of the Drosophila gut proteome upon infection by Gram-negative bacteria which can be the basis of future proteomic analysis of the enteric immune response

EPFL2019

Circadian rhythm and cell cycle

Rosamaria Cannavo

Circadian rhythms are biological processes found in most living organisms, displaying a roughly 24-hour period, responding primarily to light darkness cycles in an organism's environment. At the cellular level, the circa-24h rhythmicity is generated by a molecular clock based on a transcription-translation feedback network and consists of a cell-autonomous and self-sustained oscillator. In conditions where cells proliferate, the cell division cycle can be also considered as an oscillator. Since both processes run with similar periods in several mammalian cells, it is reasonable to expect that interactions between these two cycles may cause synchronization. Many studies reported evidences of interactions between the circadian and the cell cycles in different organisms. In particular, it appeared that in several systems, specific cell cycle phases occur in distinct temporal windows rather than being randomly distributed in time. These findings led to the concept of circadian gating of the cell cycle, through which the circadian clock can favor or forbid cell cycle transitions at specific circadian phases. However, it was also reported the converse, namely an effect of cell division on the circadian oscillator. Even though interactions between the circadian clock and the cell cycle have been identified in both directions, the dynamical consequences and the directionality of the coupling at the single-cell level were not extensively investigated. In order to better characterize the potential synchronization in mammalian cells, we estimated the mutual interactions between circadian clock and cell cycle in NIH3T3 mouse fibroblasts by the use of time-lapse fluorescent microscopy in combination with statistical analysis and mathematical modeling. NIH3T3 cells, harboring a fluorescent reporter under the control of the circadian RevErb-a gene promoter, were imaged for several days allowing the simultaneous detection of circadian oscillations and time of divisions. The analysis of thousands of circadian cycles in dividing cells indicated that both oscillators are synchronized, with cell divisions occurring about 5 h before the peak of the circadian RevErb-a reporter. We tested several perturbations such as different serum concentrations, different temperatures, treatment with pharmacological compounds and shRNA-mediated knockdown of circadian regulators. Surprisingly, this showed that circadian rhythm and cell cycle remain synchronized over the wide range of conditions probed. Our data showed that this synchronization state reflects an unexpected predominant influence of the cell cycle on the circadian oscillator, and did not support the leading hypothesis about a circadian gating of the cell cycle. The stochastic modeling of two interacting phase oscillators allowed us to identify the parameters of the coupling functions, revealing an acceleration of circadian phase after the division. The work presented in this thesis sheds light on the interaction between two fundamentally recurrent cellular processes in mammalian cells and provides a deeper understanding of the role of the circadian clock in proliferating cells and tissues. These findings might have significant implications for chronobiology and chronotherapeutics.

EPFL2016

Dissecting Gene Regulatory Networks Using Targeted Quantitative Proteomics

Jovan Simicevic

Gene regulatory networks control gene expression levels, and therefore play an essential role in mammalian development and function. Regulation of gene expression is the result of a complex interplay between DNA regulatory elements and their binding partners, known as transcription factors (TFs). Due to their vital role in development, intercellular signalling, cell cycle and disease development, elucidating the mechanisms by which TFs regulate gene expression is of crucial importance in the vast majority of biological processes. In particular, understanding how each TF contributes to the expression output of its respective target gene in space and time will help to elucidate how gene regulatory networks (GRNs) behave under different physiological or pathological conditions. Although extensive work has been accomplished in characterizing the key TFs involved in many biological processes, almost no quantitative information is currently available in the literature. To get a deep insight into the complex mechanisms underlying the regulation of gene expression, we need to acquire quantitative information, since TF abundance within the cell can be linked to their transcriptional capabilities. Such information would be of utmost importance to build accurate in silico quantitative DNA binding models that could predict and explain the particular properties of gene regulatory mechanisms. The quantification of TFs is a difficult task due their natural low abundance in cells, and their reliable detection is therefore very much dependent on the overall sensitivity of current technologies. In recent years, a new MS-based technology termed selected reaction monitoring (SRM) has gained popularity due to the targeted nature of its approach that allows the detection and quantification of proteins in complex samples with an exceptional sensitivity and specificity. I will show in this thesis, this approach is particularly well suited for targeting low abundant proteins such as TFs, which are otherwise difficult to identify with conventional shotgun proteomics experiments. Consequently, the main focus of my thesis research project entailed the development of an SRM-based platform aimed at quantifying TFs in absolute amounts based on in vitro protein expression during the terminal stage of adipogenesis, using the pre-adipocyte 3T3-L1 cell line. Interestingly, our initial efforts led to the creation of an atlas of TF-specific peptide data, which could be readily used for the design of quantitative assays. In the first phase, abundance measurements in terms of copies per cell were derived at precise differentiation time-points for two major adipogenic players, PPARγ and RXRα. In the second phase, we expanded the number of adipogenic TFs that can be monitored in one assay, allowing for the quantification of up to 10 TFs in one single, integrated SRM run. Such upscale increases the practical usefulness of the methodology while reducing the associated costs, and ultimately allows for non-negligible time-savings. The availability of absolute protein copy number data permitted us ultimately to examine the relationship between the number of genome-wide DNA binding events and TF molecules. We derived a quantitative DNA binding model that allowed the prediction of the number of PPARγ ChIP-seq binding events given its nuclear abundance, chromatin state, and DNA binding energetics. As such, we were able to explain the paradoxical observation of a significant increase in PPARγ binding sites despite a saturation in the number of PPARγ molecules. We thus demonstrate how TF abundance data can be modeled in conjunction with large-scale DNA occupancy and chromatin state data to further our understanding of gene regulatory mechanisms mediating cellular differentiation. We are now starting to build on our pioneering work to quantify in absolute terms key players of the entire, core adipogenic GRN, as such aiming to provide a quantitative explanation of the regulatory mechanisms at play during the terminal phase of adipocyte differentiation. Moreover, to increase the explicative power of our methodology and to alleviate the throughput limitation that comes with obtaining absolute protein measurements, we decided to perform copy-number estimates for a larger set of adipogenic TFs utilizing a modified version of our original approach. At the cost of a modest loss of accuracy, we are now aiming to develop a sensitive and robust methodology that will allow the quantification of entire GRNs at low cost and in a time-effective manner. This is consistent with the overall goal in life sciences or clinical research to improve our ability to accurately and reproducibly quantify entire pathways or biological networks to improve our systems understanding of biological processes.

EPFL2012