An agent-based model of monocyte differentiation into tumour-associated macrophages in chronic lymphocytic leukemia.

Monocyte-derived macrophages help maintain tissue homeostasis and defend the organism against pathogens. In tumors, recent studies have uncovered complex macrophage populations, including tumor-associated macrophages, which support tumorigenesis through cancer hallmarks such as immunosuppression, angiogenesis, or matrix remodeling. In the case of chronic lymphocytic leukemia, these macrophages are known as nurse-like cells (NLCs) and they protect leukemic cells from spontaneous apoptosis, contributing to their chemoresistance. We propose an agent-based model of monocyte differentiation into NLCs upon contact with leukemic B cells in vitro. We performed patient-specific model optimization using cultures of peripheral blood mononuclear cells from patients. Using our model, we were able to reproduce the temporal survival dynamics of cancer cells in a patient-specific manner and to identify patient groups related to distinct macrophage phenotypes. Our results show a potentially important role of phagocytosis in the polarization process of NLCs and in promoting cancer cells' enhanced survival.

Insights on TAM Formation from a Boolean Model of Macrophage Polarization Based on In Vitro Studies.

The tumour microenvironment is the surrounding of a tumour, including blood vessels, fibroblasts, signaling molecules, the extracellular matrix and immune cells, especially neutrophils and monocyte-derived macrophages. In a tumour setting, macrophages encompass a spectrum between a tumour-suppressive (M1) or tumour-promoting (M2) state. The biology of macrophages found in tumours (Tumour Associated Macrophages) remains unclear, but understanding their impact on tumour progression is highly important. In this paper, we perform a comprehensive analysis of a macrophage polarization network, following two lines of enquiry: (i) we reconstruct the macrophage polarization network based on literature, extending it to include important stimuli in a tumour setting, and (ii) we build a dynamical model able to reproduce macrophage polarization in the presence of different stimuli, including the contact with cancer cells. Our simulations recapitulate the documented macrophage phenotypes and their dependencies on specific receptors and transcription factors, while also unravelling the formation of a special type of tumour associated macrophages in an in vitro model of chronic lymphocytic leukaemia. This model constitutes the first step towards elucidating the cross-talk between immune and cancer cells inside tumours, with the ultimate goal of identifying new therapeutic targets that could control the formation of tumour associated macrophages in patients.

CovMulNet19, Integrating Proteins, Diseases, Drugs, and Symptoms: A Network Medicine Approach to COVID-19.

Introduction: We introduce in this study CovMulNet19, a comprehensive COVID-19 network containing all available known interactions involving SARS-CoV-2 proteins, interacting-human proteins, diseases and symptoms that are related to these human proteins, and compounds that can potentially target them. Materials and Methods: Extensive network analysis methods, based on a bootstrap approach, allow us to prioritize a list of diseases that display a high similarity to COVID-19 and a list of drugs that could potentially be beneficial to treat patients. As a key feature of CovMulNet19, the inclusion of symptoms allows a deeper characterization of the disease pathology, representing a useful proxy for COVID-19-related molecular processes. Results: We recapitulate many of the known symptoms of the disease and we find the most similar diseases to COVID-19 reflect conditions that are risk factors in patients. In particular, the comparison between CovMulNet19 and randomized networks recovers many of the known associated comorbidities that are important risk factors for COVID-19 patients, through identified similarities with intestinal, hepatic, and neurological diseases as well as with respiratory conditions, in line with reported comorbidities. Conclusion: CovMulNet19 can be suitably used for network medicine analysis, as a valuable tool for exploring drug repurposing while accounting for the intervening multidimensional factors, from molecular interactions to symptoms.

Structural and Energetic Characterization of the Ankyrin Repeat Protein Family.

Ankyrin repeat containing proteins are one of the most abundant solenoid folds. Usually implicated in specific protein-protein interactions, these proteins are readily amenable for design, with promising biotechnological and biomedical applications. Studying repeat protein families presents technical challenges due to the high sequence divergence among the repeating units. We developed and applied a systematic method to consistently identify and annotate the structural repetitions over the members of the complete Ankyrin Repeat Protein Family, with increased sensitivity over previous studies. We statistically characterized the number of repeats, the folding of the repeat-arrays, their structural variations, insertions and deletions. An energetic analysis of the local frustration patterns reveal the basic features underlying fold stability and its relation to the functional binding regions. We found a strong linear correlation between the conservation of the energetic features in the repeat arrays and their sequence variations, and discuss new insights into the organization and function of these ubiquitous proteins.

Amino Acid metabolism conflicts with protein diversity.

The 20 protein-coding amino acids are found in proteomes with different relative abundances. The most abundant amino acid, leucine, is nearly an order of magnitude more prevalent than the least abundant amino acid, cysteine. Amino acid metabolic costs differ similarly, constraining their incorporation into proteins. On the other hand, a diverse set of protein sequences is necessary to build functional proteomes. Here, we present a simple model for a cost-diversity trade-off postulating that natural proteomes minimize amino acid metabolic flux while maximizing sequence entropy. The model explains the relative abundances of amino acids across a diverse set of proteomes. We found that the data are remarkably well explained when the cost function accounts for amino acid chemical decay. More than 100 organisms reach comparable solutions to the trade-off by different combinations of proteome cost and sequence diversity. Quantifying the interplay between proteome size and entropy shows that proteomes can get optimally large and diverse.

A Cyclin T1 point mutation that abolishes positive transcription elongation factor (P-TEFb) binding to Hexim1 and HIV tat.

BACKGROUND: The positive transcription elongation factor b (P-TEFb) plays an essential role in activating HIV genome transcription. It is recruited to the HIV LTR promoter through an interaction between the Tat viral protein and its Cyclin T1 subunit. P-TEFb activity is inhibited by direct binding of its subunit Cyclin T (1 or 2) with Hexim (1 or 2), a cellular protein, bound to the 7SK small nuclear RNA. Hexim1 competes with Tat for P-TEFb binding. RESULTS: Mutations that impair human Cyclin T1/Hexim1 interaction were searched using systematic mutagenesis of these proteins coupled with a yeast two-hybrid screen for loss of protein interaction. Evolutionary conserved Hexim1 residues belonging to an unstructured peptide located N-terminal of the dimerization domain, were found to be critical for P-TEFb binding. Random mutagenesis of the N-terminal region of Cyclin T1 provided identification of single amino-acid mutations that impair Hexim1 binding in human cells. Furthermore, conservation of critical residues supported the existence of a functional Hexim1 homologue in nematodes. CONCLUSIONS: Single Cyclin T1 amino-acid mutations that impair Hexim1 binding are located on a groove between the two cyclin folds and define a surface overlapping the HIV-1 Tat protein binding surface. One residue, Y175, in the centre of this groove was identified as essential for both Hexim1 and Tat binding to P-TEFb as well as for HIV transcription.

A single point mutation in cyclin T1 eliminates binding to Hexim1, Cdk9 and RNA but not to AFF4 and enforces repression of HIV transcription.

BACKGROUND: Human immunodeficiency virus (HIV) gene expression is primarily regulated at the step of transcription elongation. The viral Tat protein recruits the Positive Transcription Elongation Factor b (P-TEFb) and the Super Elongation Complex (SEC) to the HIV promoter and enhances transcription by host RNA polymerase II. RESULTS: To map residues in the cyclin box of cyclin T1 that mediate the binding of P-TEFb to its interacting host partners and support HIV transcription, a pool of N-terminal cyclin T1 mutants was generated. Binding and functional assays in cells identified specific positions in cyclin T1 that are important for (i) association of P-TEFb with Hexim1, Cdk9 and SEC/AFF4 (ii) supporting Tat-transactivation in murine cells and (iii) inhibition of basal and Tat-dependent HIV transcription in human cells. Significantly, a unique cyclin T1 mutant where a Valine residue at position 107 was mutated to Glutamate (CycT1-V107E) was identified. CycT1-V107E did not bind to Hexim1 or Cdk9, and also could not assemble on HIV TAR or 7SK-snRNA. However, it bound strongly to AFF4 and its association with HIV Tat was slightly impaired. CycT1-V107E efficiently inhibited HIV replication in human T cell lines and in CD4(+) primary cells, and enforced HIV transcription repression in T cell lines that harbor a transcriptionally silenced integrated provirus. CONCLUSIONS: This study outlines the mechanism by which CycT1-V107E mutant inhibits HIV transcription and enforces viral latency. It defines the importance of N-terminal residues of cyclin T1 in mediating contacts of P-TEFb with its transcription partners, and signifies the requirement of a functional P-TEFb and SEC in mediating HIV transcription.

Detection of small tendon lesions by sonoelastographic visualization of strain profile differences: initial experiences.

PURPOSE: To assess the capability of a commercial sonoelastography system to detect small tendon lesions by quantitative analysis of elastogram profiles. MATERIALS AND METHODS: Strips of equine digital flexor tendons were used to model small human tendons. Two tendons were examined. From each tendon, six unmodified tendon strips (controls) and six tendon strips with a central defect of the same tendons were compared. The tendon strips were placed under a physiological tensile strain of 5%. Sonoelastographic visualization of the strain profile was performed. Regions of interest (ROI) were defined left and right of the tendon defects. Average tissue strains in these ROI were compared with tissue strain in controls. RESULTS: In the first series of experiments, there was a significant (p = 0.011) difference in the strain profile in regions proximal and distal to the tendon lesions compared with the respective tendon areas in the control tendon strips. In a second series of experiments, similar trends were observed, but the differences were not significant (p = 0.824). CONCLUSION: Even under carefully controlled experimental conditions using computational post-processing of sonoelastograms, tendon lesions could only be partially detected within elastograms from a clinical sonoelastography system. The ability to detect differences in some strain profiles indicates that tensile sonoelastography has the potential to identify small tendon lesions (such as those in the hand), but that substantial improvements with respect to quantitative analysis are required to make such measures diagnostically relevant.

Evolution of 7SK RNA and its protein partners in metazoa.

7SK RNA is a key player in the regulation of polymerase II transcription. 7SK RNA was considered as a highly conserved vertebrate innovation. The discovery of poorly conserved homologs in several insects and lophotrochozoans, however, implies a much earlier evolutionary origin. The mechanism of 7SK function requires interaction with the proteins HEXIM and La-related protein 7. Here, we present a comprehensive computational analysis of these two proteins in metazoa, and we extend the collection of 7SK RNAs by several additional candidates. In particular, we describe 7SK homologs in Caenorhabditis species. Furthermore, we derive an improved secondary structure model of 7SK RNA, which shows that the structure is quite well-conserved across animal phyla despite the extreme divergence at sequence level.