key: cord-0299426-qkjvzbdk
authors: Smirlis, Despina; Dingli, Florent; Sabatet, Valentin; Roth, Aileen; Knippchild, Uwe; Loew, Damarys; Späth, Gerald F.; Rachidi, Najma
title: SILAKin: A novel high throughput SILAC and mass spectrometry-based assay to identify the substratome of kinases secreted by pathogens
date: 2021-05-05
journal: bioRxiv
DOI: 10.1101/2021.05.05.442720
sha: cc9ba4a93eec9bedcb3f80c618f99ed211e3f9d0
doc_id: 299426
cord_uid: qkjvzbdk

Protein phosphorylation is one of the most important reversible post-translational modifications. It affects every cellular process including differentiation, metabolism and cell cycle. Eukaryotic protein kinases (ePK) catalyse the transfer of a phosphate from ATP onto proteins, which regulates fast changes in protein activity, structure or subcellular localisation. The systematic identification of substrates is thus crucial to characterise the functions of kinases and determine the pathways they regulate, and even more so when studying the impact of pathogens-excreted kinases on the host cell signal transduction. Several strategies and approaches have been used to identify substrates, but all show important limitations thus calling for the development of new efficient and more convenient approaches for kinase substrate identification. Herein, we present SILAkin, a novel and easy method to identify substrates that is applicable to most kinases. It combines phosphatase treatment, pulse heating, in vitro kinase assay (IVKA) and SILAC (Stable Isotope Labeling with Amino acids in Cell culture)-based quantitative mass spectrometry (MS). We developed SILAkin using the Leishmania casein kinase 1 (L-CK1.2) as experimental model. Leishmania, an intracellular parasite causing Leishmaniasis, releases L-CK1.2 in its host cell. Applying this novel assay allowed us to gain unprecedented insight into host-pathogen interactions through the identification of host substrates phosphorylated by pathogen-excreted kinases. We identified 225 substrates, including 85% previously unknown that represent novel mammalian CK1 targets, and defined a novel CK1 phosphorylation motif. The substratome was validated experimentally by L-CK1.2 and human CK1δ, demonstrating the efficiency of SILAkin to identify new substrates and revealing novel regulatory pathways. Finally, SILAkin was instrumental in highlighting host pathways potentially regulated by L-CK1.2 in Leishmania-infected host cells, described by the GO terms ‘viral & symbiotic interaction’, ‘apoptosis’, ‘actin cytoskeleton organisation’, and ‘RNA processing and splicing’. SILAkin thus can generate important mechanistic insights into the signalling of host subversion by these parasites and other microbial pathogen adapted for intracellular survival.

Protein phosphorylation, one of the essential reversible post-translational modifications, affects every cellular process including transport, metabolism and DNA repair [reviewed in 1 ] . Eukaryotic protein kinases (ePK) catalyse the transfer of a phosphate from ATP onto proteins to regulate fast changes in protein activity, structure, interaction, or subcellular localisation. ePKs target proteins through kinasespecific recognition motif, which allows for specificity and restricts the number of their substrates.

The systematic identification of substrates is thus crucial to characterise the functions of kinases and determine the pathways they regulate -even more so when studying the impact of pathogens-derived kinases on the host cell signal transduction during intracellular infection, for instance, by viral and bacterial pathogens 2 . However, the low stoichiometry of protein phosphorylation, the presence of endogenous kinases as well as the reversibility of the phosphorylation by phosphatases render systematic mapping of the cellular substratome extremely challenging. This is particularly true when handling pleiotropic signalling kinases such as casein kinase 1 (CK1), able to phosphorylate hundreds of substrates 3 , or investigating pathogen-excreted kinases that are low in abundance and compete with high-abundant host kinases thus precluding the identification of de novo phosphorylation events by these exo-kinases.

Several strategies and approaches have been developed and applied to identify substrates (for review see 4 ) , including (i) genetic screens 5, 6 , (ii) protein and peptide arrays 7, 8 , (iii) phage display 9, 10 , (iv) KinasE Substrate TRacking and ELucidation (KESTREL) 11 , (v) Kinase-Interacting Substrate Screening (KISS) 12 , (vi) chemical-genetic methods with genetically engineered kinases 13 and (vii) quantitative phosphoproteomics in intact cells 14, 15 . Although these approaches allowed the identification of an important number of substrates, but all show important limitations, which include bottlenecks inherent to high-throughput mutagenesis in genetic screens; laborious process and lowthroughput screening for KESTREL; unstable interactions for KISS or the low catalytic efficiency of certain engineered kinases for chemical-genetic screens. Thus there is an urgent need to develop new easy and efficient approaches for kinase substrate identification, especially since the most important human diseases such as cancer or neurodegenerative diseases are linked to deregulation, or mutations of kinases 16 .

Here, we pioneered a novel technology, applicable to most protein kinases, termed SILAkin that allows for easy and efficient identification of substrates. Applied to intracellular macrophage infection with the protozoan pathogen Leishmania, we identified host substrates that shed important new light on parasite immune subversion and validate SILAkin as a powerful new tool to study mechanisms of host/pathogen interaction.

Pathogens that invade mammalian host cells export proteins and particularly kinases via exosomes to modify their host cell 17, 18 . Identification of host substrates for these exo-kinases could be particularly challenging, as only a small fraction of the kinase pool is exported, and exosomes represent a complex environment containing many proteins, including other kinases that could mask substrate phosphorylation by the kinase of interest (KOI). We thus developed a method to identify host substrates of pathogen kinases, irrespective of their abundance and the complexity of the environment.

As a proof of principle, we identified the host substrates of L-CK1.2, released by Leishmania parasites 18, 19 ; since little is known about the pathways it regulates in macrophages. Leishmania is an intracellular parasite that resides in the parasitophorus vacuole of macrophages and subvert its host cell to survive.

To identify the L-CK1.2 host-substratome, we implemented an experimental workflow designed to quantify phospho-peptide stoichiometry by LC/MS-MS, in metabolically-labelled, heat inactivated THP-1 macrophage protein lysates after their phosphorylation by recombinant L-CK1.2 (Fig.1A) .

Because CK1 recognises consensus sites that require or not priming by upstream kinases, prior in vitro kinase assay (IVKA), we depleted the lysates in ATP before treating them or not with Antarctic phosphatase. Dephosphorylation of existing phospho-sites increased the number of sites available for de novo L-CK1.2 phosphorylation. Phospho-peptide stoichiometry was calculated from technical triplicate as a ratio of Heavy L-CK1.2 /Light L-CK1.2-K40A and comparisons were made to phospho-peptide ratios of Heavy/Light mock reactions without kinases.

For establishing appropriate experimental conditions, several pilot experiments were carried out. To decrease the background activity of endogenous kinases, the lysate of THP-1 macrophages was pulseheated to denature endogenous kinases (Fig. S1) . Denaturation efficiency was demonstrated by the absence of 32 P incorporation in the background control (Fig. S1, lane 2) . In contrast, the de novo phosphorylation of denatured THP-1 proteins by active L-CK1.2 was detected, showing that L-CK1.2 phosphorylates proteins present in the macrophage lysate (Fig. S1, lane 1) . To increase the number of sites available for de novo phosphorylation in the macrophage lysate, two steps were added to the pipeline (Fig. 1A) . Free ATP was depleted from protein lysates by dialysis to prevent any phosphorylation while the samples were dephosphorylated by Antarctic phosphatase. The increase of 32 P incorporation into substrates following phosphatase treatment ( Figure S1 , lane 3) confirms that previously many sites were inaccessible to de novo phosphorylation. To reduce technical errors during sample preparation for MS, limit missing values and perform quantitative analyses, we used Stable Isotope Labelling with Amino acids in Cell culture (SILAC). This method relies on the metabolic incorporation of either "Heavy" [ 2 H 4 -Lysine (Lys 4 ) and 13 C 6 -Arginine (Arg 6 )] or natural ("Light")

[lysine (Lys 0 ) and arginine (Arg 0 )] amino acids 20, 21 . We validated by LC-MS/MS analysis the percentage of incorporation of Lys 4 and Arg 6 in macrophage proteins. This analysis revealed that more than 99 % of the identified peptides contained the two heavy amino acids. Finally, to reduce the risk of selecting false positive signals, we performed mock kinase assays using the "light" and "heavy" macrophage lysates without adding the kinases, to discard sites already differentially phosphorylated prior to the kinase assays.

Three independent reactions for each condition were carried out, and two independent protein extracts treated or not with phosphatase were used. In the absence of phosphatase treatment, 7,752 unique phosphopeptides belonging to 3,544 unique proteins were identified of which 65% were quantified (see Fig.S2A&B for Venn diagrams). The same analysis was performed with samples pre-treated with phosphatase, and 15,852 phosphopeptides (5,158 proteins) were identified of which 66% were quantified (Fig.S2C&D) , demonstrating the efficiency of the phosphatase treatment. However, the increase in phospho-peptides also in the H/L control (Fig.S2A&B) suggests that the pulse-heating step did not completely abrogate but only reduced the activity of endogenous kinases to levels undetectable by autoradiography (Fig.S1 ).

To determine L-CK1.2 substrates, the following selection criteria were applied: (i) A probability of correct localisation of the phosphorylation site on validated peptides greater than 75%, as calculated Table 1) . Only fifteen proteins were common to the two datasets. Although consistent with the stochasticity of the LC/MS analysis, this finding suggests that the phosphatase treatment greatly improves the access of L-CK1.2 to new substrates for which it has more affinity.

Three levels of validation were used to demonstrate that the dataset containing 225 proteins are bona fide host L-CK1.2 substrates ( Table 2) . First, we identified 11 known human CK1 substrates, including the interferon-alpha/beta receptor alpha chain (IFNAR1) 22 , Sprouty 2 (SPRY2) 23 and Fam83H 24 as well as 66 known CK1 binding partners, which thus might also be substrates. Second, we showed that the phosphorylated peptides were highly enriched in known CK1 consensus sites 25 Fig. 1B top panel) , consistent with the affinity of CK1 for these two motifs [26] [27] [28] [29] [30] [31] [32] [33] . Seventy-four sites display the non-canonical consensus SLS-Xn-(E/D)n 29, 34-36 or resemble to K/R(X)K/R(XX)pS/pT, a CK1 consensus site identified in cholesterol and sulfatide binding proteins ( Table 1, Fig. 1B middle panel) 37 . Surprisingly, this motif was present in only 10 phosphopeptides while the remaining 58 peptides contained a shorter version, K/R(XX)pS/pT. Finally, seventy-seven phospho-sites did not contain any known CK1 motif (others, Table 1 ), and might represent novel mammalian CK1 phosphorylation motif (Table 1) . Indeed, we identified

[G]XX[pS/pT] in 13 phospho-peptides ( Fig. 1B bottom panel and Table 3 ). Noticeably, all the consensus sites identified in this study have a proline residue adjacent to the phosphorylated S or T, (Fig. 1B, position 7) , which was not described for other CK1s. In that, it resembles the phosphorylation motif phosphorylated by CDKs 38 , and might be a characteristic of L-CK12 substrate recognition. Third, experimental validation of the phosphoproteomics analyses was carried out by the implementation of an in vitro kinase assay (IVKA) using purified human recombinant proteins, as substrates. We included five proteins that might be important for Leishmania intracellular survival based on their potential to modulate macrophage functions and/or inflammation. The selected recombinant proteins, namely reticulocalbin 2 (RCN2, Q14257), 14-3-3γ (YWHAG, P61981), lactoylglutathione lyase 1 (Glo1, Q04760), synaptosomal-associated prot 23 (SNAP23, O00161) and transcription initiation factor TFIID subunit 7 (TAF7, Q15545) were subjected to a kinase assay using inactive L-CK1.2-K40A (kinase-dead), active L-CK1.2 alone or in presence of the CK1-specific small molecule inhibitor D4476 39 . All recombinant proteins were phosphorylated by L-CK1.2, but no phosphorylation was observed in the D4476 and L-CK1.2-K40A controls (Fig. 1C) . All L-CK1.2 substrates tested were also phosphorylated by CK1δ, confirming the relevance of our substratome for human CK1s (Fig. 1D) . Altogether, these results confirm that our dataset identified bona fide L-CK1.2 host cell substrates, which validate the SILAkin method. Furthermore these substrates are potentially also targeted by human CK1δ, revealing novel targets and thus new pathways regulated by human CK1δ.

Because SILAkin is an in vitro method, the question of physiological relevance needed to be addressed. To this end, our dataset was compared to human cell phospho-proteomes to determine whether any of the 257 phospho-sites were phosphorylated in vivo. 94% were identified in various phospho-proteomes ( Table 1 and S1, https://www.phosphosite.org/homeAction.action), suggesting that the phospho-sites identified by SILAkin are physiologically relevant. Our data allow the attribution of those sites to human CK1. Similarly, we investigated whether any L-CK1.2 substrates were described as differentially regulated in human diseases. Indeed, 89% of phospho-sites are phosphorylated in cancer cells (Table 1&S1 and Fig.2, round shape) and 10% are mutated during tumorigenesis (Table 1&S1 and Fig.2, red border) . Moreover, 76% of the L-CK1.2 substrates are considered as prognosis markers for various cancer types (Table 1&S1) . These data are consistent with the fact that human CK1 isoforms are overexpressed in cancer cells 25, 40 and often contribute to chemo-and apoptosis resistance as well as to a reduction of overall survival of patients 25 . Regarding infectious diseases, we showed that 51% of L-CK1.2 substrates are phosphorylated during SARS-CoV2 infection (Fig. 2, green) , and 20% on the same sites as those phosphorylated by L-CK1.2 (Table 1&S1) . Surprisingly, only two GO processes are enriched, 'RNA splicing' and 'cellular localisation and transport' in the substrates phosphorylated by L-CK1.2 and SARS-CoV2 infection ( Fig. S3 and Table S2&S3 ), suggesting that SARS-CoV2 and Leishmania might similarly exploit these two processes and that SARS-CoV2 might exploit CK1 pathways for its replication. Our data demonstrate the potential impact of CK1 in SARS-CoV2 infection, which is consistent with the role of host CK1 in viral replication 41 42-44 .

Although obtained in vitro, the substratome is enriched in proteins physiologically relevant for Leishmania infection (60% total) and might give us important insights into the mechanisms developed by Leishmania to subvert its host cell. Indeed, during Leishmania infection, 32% of L-CK1.2 substrates were shown to be differentially regulated at protein level [45] [46] [47] [48] , while 30% were differentially expressed at transcript level [49] [50] [51] [52] (Table 1) . In the substratome, we identified functional enrichment for GO terms relative to apoptosis or RNA processing and splicing, which is consistent with Leishmania inhibiting host apoptosis 53, 54 or modifying the host transcriptome, respectively 49, 55 (Fig. 3) .

Moreover, several key processes, preferentially targeted by Leishmania CK1.2, are associated with host-pathogen interactions such as 'viral and symbiotic interaction' or 'cellular response stimulus' (Fig. 3, Table S4 ). Lastly, the identification of processes such as 'positive regulation of metabolic process', 'positive regulation of molecular function activity' and 'GTPase signal transduction', are consistent with L-CK1.2 being a signalling kinase (Fig. 3, Table S4 ). Altogether, its functional characterisation supports the physiological relevance of the substratome, while revealing the pathways that might be regulated by L-CK1.2 during Leishmania infection. These pathways should be investigated in priority to decipher L-CK1.2 functions in the host cell.

Increasing the knowledge on kinases and particularly the pathways they regulate is crucial to better understand cellular functions, hence the importance of finding their substrates in an unbiased manner.

It is even more important when studying host cell signalling pathways exploited by pathogens during infection through the release of their kinases. Many high throughput methods exist and most of them have important drawbacks or are not adapted to host-pathogen interaction studies 56 . Here, we propose SILAkin, a novel, easy, and validated method applicable to most kinases from any organism that overcomes most of the limitations existing in other mass spectrometry-based methods: First, it allows direct detection of phosphorylation, contrary to phospho-proteomics comparing WT and mutant kinase compartments 39, 57 , and recognises specific consensus sites, the limitations inherent to IVKA do not apply. L-CK1.2 is therefore the perfect kinase to demonstrate the efficiency of SILAkin.

Our large dataset allowed us to refine existing CK1 substrate recognition motif such as K/R(X)K/R(XX)pS/pT, for which we proposed a shorter version, K/R(XX)pS/pT 37 ; and to define a novel CK1 consensus site such as [G]X 2-3 [pS/pT], validated experimentally with L-CK1.2 and CK1δ (SNAP23, Fig. 1C and D) . Further analyses, including mutagenesis, will be required to confirm this new consensus, as we cannot exclude the possibility that SNAP23 was phosphorylated on another site. In conclusion, we developed a method sufficiently sensitive to reveal substrates phosphorylated by pathogen-excreted kinases, allowing us to gain insights into host-pathogen interactions.

For labelling cells by SILAC, equal numbers of THP-1 monocytes (2*10 5 ml -1 ) were seeded in RPMI 

Bacterial expression plasmid for L-CK1.2 was generated as previously described 62 

Unique phospho-peptides sequences, matching the strict selection criteria, were aligned on phosphorylated serine and threonine with 5 flanking amino acids. PhosphoSitePlus phosphosite plus (https://www.phosphosite.org/homeAction.action 68 ) , was used to compute motif analysis enrichment (automatic background selection; significance of 1e-6; support threshold of 0.1) and to generate corresponding sequence logo (automatic background selection; frequency change algorithm 69 .

The dataset was analyzed for protein-protein interactions and visualized using the STRING plugin (string, https://string-db.org/ 70 ) of the Cytoscape software package (version 3.8.2, https://cytoscape.org/ 71 ). Each node represents a substrate and each edge represents a protein-protein interaction. Functional enrichment analysis of the dataset was performed using the g:profiler web server (https://biit.cs.ut.ee/gprofiler/gost) using the following criteria: only annotated genes, with a significance threshold of 0.05, select GO terms of less than 5 000 genes, and only focusing on GO 'biological process'. Results were visualized using the EnrichmentMap plugin of the Cytoscape software package (version 3.3, http://apps.cytoscape.org/apps/enrichmentmap 72 ), with a p-value and a Q-value above 0.05 and an edge cut-off of 0.375. Node color represents the enrichment p-value (see legend Figure 2 ). Node size is proportional to the total number of genes belonging to the corresponding gene-set. The edge corresponds to the Annotation shared between two nodes, with edge thickness corresponding to the number of shared genes. Node clusters were identified and annotated by the AutoAnnotate plugin of cytoscape (version 1.3.3 https://autoannotate.readthedocs.io/en/latest/). Functional enrichment analysis of the whole dataset was performed using the g:profiler web server.

Results were visualized using the EnrichmentMap plugin of the Cytoscape software package, with a pvalue and a Q-value above 0.05 and an edge cut-off of 0.375. Node colour represents the enrichment p-value. Node size is proportional to the total number of genes belonging to the corresponding geneset. The edge corresponds to the Annotation shared between two nodes (blue), with edge thickness corresponding to the number of shared genes. Node clusters were identified and annotated by the AutoAnnotate plugin of cytoscape. See Table S1 for list of the whole list of annotations. 

The crucial role of protein phosphorylation in cell signaling and its use as targeted therapy (Review)

Subversion of cell signaling by pathogens. Cold Spring Harbor perspectives in biology

The CK1 Family: Contribution to Cellular Stress Response and Its Role in Carcinogenesis

Current technologies to identify protein kinase substrates in high throughput

Caenorhabditis elegans Akt/PKB transduces insulin receptor-like signals from AGE-1 PI3 kinase to the DAF-16 transcription factor

Mapping pathways and phenotypes by systematic gene overexpression

Global analysis of protein phosphorylation in yeast

Peptide arrays for kinase profiling

MNK1, a new MAP kinase-activated protein kinase, isolated by a novel expression screening method for identifying protein kinase substrates

Catalytic specificity of phosphotyrosine kinases Blk, Lyn, c-Src and Syk as assessed by phage display

KESTREL: a powerful method for identifying the physiological substrates of protein kinases

Kinase-interacting substrate screening is a novel method to identify kinase substrates

Engineering unnatural nucleotide specificity for Rous sarcoma virus tyrosine kinase to uniquely label its direct substrates

The MAP kinase MAPKLK1 is essential to Trypanosoma brucei proliferation and regulates proteins involved in mRNA metabolism

Phosphoproteomics reveals that glycogen synthase kinase-3 phosphorylates multiple splicing factors and is associated with alternative splicing

Kinase mutations in human disease: interpreting genotype-phenotype relationships

Extracellular vesicles in parasite survival

Leishmania exosomes modulate innate and adaptive immune responses through effects on monocytes and dendritic cells

An exosome-based secretion pathway is responsible for protein export from Leishmania and communication with macrophages

Specificity of phosphorylation responses to MAP kinase pathway inhibitors in melanoma cells

Phosphoproteomic Analysis of Aurora Kinase Inhibition in Monopolar Cytokinesis

Mammalian casein kinase 1alpha and its leishmanial ortholog regulate stability of IFNAR1 and Type I interferon signaling

Casein kinase 1 regulates Sprouty2 in FGF-ERK signaling

The DUF1669 domain of FAM83 family proteins anchor casein kinase 1 isoforms

Structure, regulation, and (patho-)physiological functions of the stress-induced protein kinase CK1 delta (CSNK1D)

A type-1 casein kinase from yeast phosphorylates both serine and threonine residues of casein. Identification of the phosphorylation sites

Phosphate groups as substrate determinants for casein kinase I action

Role of acidic residues as substrate determinants for casein kinase I

Design and synthesis of two new peptide substrates for the specific and sensitive monitoring of casein kinases-1 and -2

Studies on the structural requirements of a microsomal cAMP-independent protein kinase

A synthetic beta-casein phosphopeptide and analogues as model substrates for casein kinase-1, a ubiquitous, phosphate directed protein kinase

Optimal sequences for non-phosphate-directed phosphorylation by protein kinase CK1 (casein kinase-1)--a re-evaluation

Determinants on simian virus 40 large T antigen are important for recognition and phosphorylation by casein kinase I

Mechanism of phosphorylation-dependent binding of APC to beta-catenin and its role in beta-catenin degradation

Structural features underlying the multisite phosphorylation of the A domain of the NF-AT4 transcription factor by protein kinase CK1

A noncanonical sequence phosphorylated by casein kinase 1 in beta-catenin may play a role in casein kinase 1 targeting of important signaling proteins

A Novel Consensus Phosphorylation Motif in Sulfatide-and Cholesterol-3-sulfate-Binding Protein Substrates for CK1 in Vitro

A predictive scale for evaluating cyclin-dependent kinase substrates. A comparison of p34cdc2 and p33cdk2

Pharmacological assessment defines the Leishmania donovani casein kinase 1 as a drug target and reveals important functions in parasite viability and intracellular infection

CK1alpha overexpression correlates with poor survival in colorectal cancer

The down-regulation of casein kinase 1 alpha as a host defense response against infectious bursal disease virus infection

The flaviviral methyltransferase is a substrate of Casein Kinase 1

T-antigen kinase inhibits simian virus 40 DNA replication by phosphorylation of intact T antigen on serines 120 and 123

Structural and molecular basis of interaction of HCV non-structural protein 5A with human casein kinase 1alpha and PKR

SILAC-based quantitative proteomics reveals pleiotropic, phenotypic modulation in primary murine macrophages infected with the protozoan pathogen Leishmania donovani

Proteomic-based approach to gain insight into reprogramming of THP-1 cells exposed to Leishmania donovani over an early temporal window

Proteome profiling of human cutaneous leishmaniasis lesion

3rd Tandem Mass Tag Proteomic Analysis of in Vitro and in Vivo Models of Cutaneous Leishmaniasis Reveals Parasite-Specific and Nonspecific Modulation of Proteins in the Host

Dual Transcriptome Profiling of <em>Leishmania</em>-Infected Human Macrophages Reveals Distinct Reprogramming Signatures

Simultaneous transcriptional profiling of Leishmania major and its murine macrophage host cell reveals insights into host-pathogen interactions

Autophagic digestion of Leishmania major by host macrophages is associated with differential expression of BNIP3, CTSE, and the miRNAs miR-101c, miR-129, and miR-210

Comparative analysis of resistant and susceptible macrophage gene expression response to Leishmania major parasite

Intracellular infection by Leishmania donovani inhibits macrophage apoptosis

Leishmania donovani inhibits macrophage apoptosis and pro-inflammatory response through AKT-mediated regulation of beta-catenin and FOXO-1

Transcriptional signatures of BALB/c mouse macrophages housing multiplying Leishmania amazonensis amastigotes

The significant others: Global search for direct kinase substrates using chemical approaches

The low complexity regions in the C-terminus are essential for the subcellular localisation of <em>Leishmania</em> casein kinase 1 but not for its activity. bioRxiv

The Global Phosphorylation Landscape of SARS-CoV-2 Infection

SILAC-based quantitative proteomics reveals pleiotropic, phenotypic modulation in primary murine macrophages infected with the protozoan pathogen Leishmania donovani

Control of simian virus 40 DNA replication by the HeLa cell nuclear kinase casein kinase I

Identification of host-dependent survival factors for intracellular Mycobacterium tuberculosis through an siRNA screen

Probing druggability and biological function of essential proteins in Leishmania combining facilitated null mutant and plasmid shuffle analyses

From Drug Screening to Target Deconvolution: a Target-Based Drug Discovery Pipeline Using Leishmania Casein Kinase 1 Isoform 2 To Identify Compounds with Antileishmanial Activity

Integrity of the actin cytoskeleton of host macrophages is essential for Leishmania donovani infection

Pharmacological assessment defines Leishmania donovani casein kinase 1 as a drug target and reveals important functions in parasite viability and intracellular infection

myProMS, a web server for management and validation of mass spectrometry-based proteomic data

The PRIDE database and related tools and resources in 2019: improving support for quantification data

2014: mutations, PTMs and recalibrations

Two Sample Logo: a graphical representation of the differences between two sets of sequence alignments

STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets

Cytoscape: a software environment for integrated models of biomolecular interaction networks

Enrichment map: a networkbased method for gene-set enrichment visualization and interpretation