Reconstruction of tissue-specific genome-scale metabolic models for human cancer stem cells

Cancer Stem Cells (CSCs) contribute to cancer aggressiveness, metastasis, chemo/radio-therapy resistance, and tumor recurrence. Recent studies emphasized the importance of metabolic reprogramming of CSCs for the maintenance and progression of the cancer phenotype through both the fulfillment of the energetic requirements and the supply of substrates fundamental for fast-cell growth, as well as through metabolite-induced epigenetic regulation. Therefore, it is of paramount importance to develop therapeutic strategies tailored to target the metabolism of CSCs. In this work, we built computational Genome-Scale Metabolic Models (GSMMs) for CSCs of different tissues. Flux simulations were then used to predict metabolic phenotypes, identify potential therapeutic targets, and spot already-known Transcription Factors (TFs), miRNAs and antimetabolites that could be used as part of drug repurposing strategies against cancer. Results were in accordance with experimental evidence, provided insights of new metabolic mechanisms for already known agents, and allowed for the identification of potential new targets and compounds that could be interesting for further in vitro and in vivo validation.

Generative Deep Learning for Targeted Compound Design

In the past few years, de novo molecular design has increasingly been using generative models from the emergent field of Deep Learning, proposing novel compounds that are likely to possess desired properties or activities. De novo molecular design finds applications in different fields ranging from drug discovery and materials sciences to biotechnology. A panoply of deep generative models, including architectures as Recurrent Neural Networks, Autoencoders, and Generative Adversarial Networks, can be trained on existing data sets and provide for the generation of novel compounds. Typically, the new compounds follow the same underlying statistical distributions of properties exhibited on the training data set Additionally, different optimization strategies, including transfer learning, Bayesian optimization, reinforcement learning, and conditional generation, can direct the generation process toward desired aims, regarding their biological activities, synthesis processes or chemical features. Given the recent emergence of these technologies and their relevance, this work presents a systematic and critical review on deep generative models and related optimization methods for targeted compound design, and their applications.

ViralFP: A Web Application of Viral Fusion Proteins

Viral fusion proteins are attached to the membrane of enveloped viruses (a group that includes Coronaviruses, Dengue, HIV and Influenza) and catalyze fusion between the viral and host membranes, enabling the virus to insert its genetic material into the host cell. Given the importance of these biomolecules, this work presents a centralized database containing the most relevant information on viral fusion proteins, available through a free-to-use web server accessible through the URL https://viralfp.bio.di.uminho.pt/. This web application contains several bioinformatic tools, such as Clustal sequence alignment and Weblogo, including as well a machine learning-based tool capable of predicting the location of fusion peptides (the component of fusion proteins that inserts into the host's cell membrane) within the fusion protein sequence. Given the crucial role of these proteins in viral infection, their importance as natural targets of our immune system and their potential as therapeutic targets, this web application aims to foster our ability to fight pathogenic viruses.

Going virtual and going wide: comparing Team-Based Learning in-class versus online and across disciplines

Team-based learning (TBL) is an active learning pedagogy developed for in-class sessions and based on the collaborative work of small groups of students. The increasing push to online and blended learning has enhanced the need to expand this pedagogy to a virtual environment, but little evidence has been produced on how students accept online synchronous sessions of TBL. The purpose of this study, that relies on 427 responses, is to present a comparative perspective of traditional in-class versus adapted fully synchronous online TBL and across different disciplinary fields. Students of two different academic years and different programs were surveyed for their acceptance of TBL. They were invited to answer closed-ended questions focused on their engagement in all TBL learning process and the final outcomes provided. Results obtained from this unique comparative study revealed a wide approval of TBL, regardless of the environment (online or in-class TBL sessions), scientific area of courses and student gender. The acceptance of fully online TBL sessions, in a similar way as traditional in-class sessions, could be a rationale for giving more use to the 'virtual' context. Other results corroborated previous researches on TBL, such the need of student awareness of TBL benefits to get more engaged in the process or the impact of student activities overload on the TBL process. Implications are informative for pedagogical practice.

Knowledge and Use of PEP and PrEP Among Key Populations Tested in Community Centers in Portugal

Background: Pre-exposure prophylaxis (PrEP) and post-exposure prophylaxis (PEP) have been increasingly available in Europe. Due to the high burden of HIV in key populations, these could benefit from their use. In 2016, in Portugal, an open, non-interval, prospective cohort study was established in a network of 26 community-based voluntary HIV/STI counseling and testing centers. Data collected included questions on PEP and PrEP knowledge and use. We aimed to estimate the proportion of PEP and PrEP knowledge and its use among key populations, visiting the centers between 2016 and 2019. Method and results: Individuals who self-identify as being among at least one key population for HIV, men who have sex with men (MSM), people who inject drugs (PWID), sex workers (SW), migrants, and male-to-female transgender individuals (MTF), responded to questions on PEP and PrEP knowledge and use while waiting for their test results between 2016 and 2019 (n = 12,893 for PEP; n = 10,973 for PrEP). Reported knowledge was low in all key populations for both tools: 15.7% of respondents reported knowing about PEP and 10.9% about PrEP over the course of 4 years. PEP was used by 1.8% and PrEP by 0.4% of the respondents, MSM being 88.9% of PrEP users, and 52.8% of PEP users. Multivariate logistic regression showed multiple factors associated with knowing the tools, including age, education, country of birth, gender, year of test, having a reactive HIV test in the same visit, reporting an STI or condomless sex in the last 12 months, and identifying with being MSM or SW. Conclusions: Knowledge and use of PEP and PrEP remain low among key populations in Portugal. The need remains to increase knowledge and use among those at risk for HIV infection.

Model-guided development of an evolutionarily stable yeast chassis

First-principle metabolic modelling holds potential for designing microbial chassis that are resilient against phenotype reversal due to adaptive mutations. Yet, the theory of model-based chassis design has rarely been put to rigorous experimental test. Here, we report the development of Saccharomyces cerevisiae chassis strains for dicarboxylic acid production using genome-scale metabolic modelling. The chassis strains, albeit geared for higher flux towards succinate, fumarate and malate, do not appreciably secrete these metabolites. As predicted by the model, introducing product-specific TCA cycle disruptions resulted in the secretion of the corresponding acid. Adaptive laboratory evolution further improved production of succinate and fumarate, demonstrating the evolutionary robustness of the engineered cells. In the case of malate, multi-omics analysis revealed a flux bypass at peroxisomal malate dehydrogenase that was missing in the yeast metabolic model. In all three cases, flux balance analysis integrating transcriptomics, proteomics and metabolomics data confirmed the flux re-routing predicted by the model. Taken together, our modelling and experimental results have implications for the computer-aided design of microbial cell factories.

Encapsulation of Pseudomonas libanensis in alginate beads to sustain bacterial viability and inoculation of Vigna unguiculata under drought stress

Conventional agricultural practices based on the application of synthetic fertilizers are increasingly considered as unsustainable. Under a forecasted scenario of drought for the next decades, there is a global demand for innovative and sustainable approaches to ameliorate plant performance. Here, encapsulating beneficial microbes (BMs) to promote plant growth is gaining attention. This study evaluates bacterial encapsulation using polymeric beads of alginate, testing the survival of Pseudomonas libanensis TR1 stored up to 90 days. Produced beads were subjected to different treatments (fresh, air-dried and pulverized), which resulted in a variable size range (1200-860 µm). After storage, bacterial viability was maintained, and air-dried beads displayed a higher number of colony-forming units (2 × 107). Then, a glasshouse experiment investigated the drought resistance (plant growth, biomass, and photosynthetic responses) of Vigna unguiculata plants inoculated with these alginate beads. After 10 days of complete water restriction, turgidity and relative water content of V. unguiculata were still high under drought stress (> 80%). Leaf and root growth and biomass did not evidence significant changes after water restriction even after P. libanensis inoculation. Plant photosynthetic parameters (stomatal conductance, net photosynthetic rate, leaf CO2 concentration, or F v'/F m') were slightly affected due to inoculation but the level of stress-induced minimal plant responses. In our experiment, water restriction might have been insufficient to downregulate photosynthetic efficiency and reduce plant growth, limiting our understanding of the role of P. libanensis inoculation in alleviating drought stress in V. unguiculata, but highlighting the important relationship between the stress level and agricultural benefits of using encapsulated BMs.

Provision of Preexposure Prophylaxis at the Portuguese National Health Service and Uptake in the Lisbon Cohort of Men Who Have Sex with Men

We aimed to study the uptake of preexposure prophylaxis (PrEP) before and after its implementation in the Portuguese National Health Service (PNHS) among men who have sex with men (MSM). We studied 6164 participants in the Lisbon Cohort of MSM who participated between March 2014 and July 2019. 198 participants (3.2%) reported having recently used PrEP. Approximately one-third started PrEP after its implementation. PrEP uptake increased from 0.15% in 2014 to 5.36% in 2019. In their first use, 86 participants (70.5%) used it daily. How PrEP was obtained varied according to the timing of the first use: prescribed by a physician in Portugal (11.1% before vs 68.8% after implementation) and online (40.7% before vs 14.1% after). We observed an increase in the uptake and in the prescription by a physician, particularly after its implementation in the PNHS representing a change to a more equitable and safer way of using PrEP.

POS0872 CLINICAL FEATURES AND OUTCOME OF 1054 PATIENTS WITH SYSTEMIC SCLEROSIS: AN ANALYSIS OF THE PORTUGUESE REUMA.PT REGISTRY FOR SCLERODERMA (REUMA.PT/SSC)

Background:

Systemic sclerosis (SSc) may present distinctive manifestations and survival in different ethnic and geographic groups.

Objectives:

To describe the clinical features, treatments, and survival of adult SSc patients registered in Reuma.pt/SSc.

Methods:

Demographic features, SSc subsets, fulfilment of classification criteria, clinical and immunologic characteristics, comorbidities, medication and deaths were reviewed. Survival was calculated for patients included in the registry within the first 2 years of diagnosis.

Results:

In total, 1054 patients were included, 87.5% female, mean age at diagnosis 52.7 ± 14.8 years. The most common subset was limited cutaneous (lc)SSc (56.3%), followed by diffuse cutaneous (dc)SSc (17.5%), preclinical SSc (13%), overlap syndrome (9.8%) and SSc sine scleroderma (3.3%). Raynaud’s phenomenon (93.4%) and skin thickening (76.9%) were the most observed manifestations. Gastrointestinal (62.8% vs 47.8%), pulmonary (59.5% vs 23%) and cardiac (12.8% vs 6.9%) involvement were significantly more prevalent in dcSSc compared to lcSSc (Table 1). 52.5% of patients were ACA positive and 21% anti-topoisomerase positive, with significant differences between lcSSc and dcSSc. One third of patients was treated with immunomodulators, 53.6% with vasodilators, 23% received glucocorticoids and 2.3% biologics.

During the median follow-up 12.4 years, 83 deaths (7.9%) were verified. The overall 1, 2 and 5 years survival was 98.0%, 96.8% and 92.6% respectively, without significant differences between lcSSc and dcSSc (Figure 1).

Conclusion:

Reuma.pt/SSc register is useful in routine patient monitoring and contributes to improve knowledge about this rare and complex disease. Clinical features of Portuguese SSc patients are similar to what has been described in other populations although the overall 5-year survival in recently diagnosed patients appears to be higher than previously reported.

Table 1.

Cumulative clinical and immunologic characteristics of Portuguese SSc patients

Clinical and immunologic featuresTotalN=1054Limited cutaneous SScN= 576 (56.3%)Diffuse cutaneous SScN=180 (17.5%)P valueSkin involvement – N(%) N=987688 (90.6)525 (90.7)180 (100)<0.01Skin thickening * – N (%) N= 962680 (76.9)512 (88.9)180 (100)<0.01Digital ulcers – N (%) N=970325(33.5)186 (34.7)4 (51.5)<0.01Raynaud’s Phenomenon – N (%) N=1010943 (93.4)539 (95.7)157 (92.4)0.06Musculoskeletal involvement – N(%) N=972346 (45.6)247 (42.7)99 (55)<0.01Cardiac involvement –N(%) – N=92471 (7.7)36 (6.9)19 (12.8)0.02Renal involvement –N(%) – N= 91717 (1.9)8!1.5)6 (4.1)0.07Gastrointestinal involvement - N(%) N=933508 (48.2)277 (47.8)113 (62.8)<0.01Pulmonary involvement – N(%) N=915261 (28.5)119 (23)88 (59.5)<0.01PAH – N(%) N= 87114 (1.6)10 (2)1 (0.7)0.23Intersticial lung disease – N(%) N=765218 (28.5)100 (22.7)75 (57.7)<0.01Antinuclear antibodies - N(%) N=1040934 (89.8)522 (90.2)154 (88.5)0.57Anti-centromere – N(%) N= 1027540 (52.6)383 (67.1)16 (9.5)<0.01Anti-Scl70 – N(%) N=1020214 (21)12 (3.3)104 (60.1)<0.01Anti-RNA polymerase III – N(%) N=71025 (3.5)12 (3.3)7 (5.6)0.38ComorbiditiesHypertension – N(%) N=431117 (27.1)76 (29.7)67 (20.7)0.1Hyperlipidemia – N(%) N=43171 (13.4)72 (12.2)24 (15.9)0.08Neoplasia – N(%) N=105429 (2.8)12 (2.1)7 (3.9)0.14

PDE-5 (phosdiasterase-5); PPIs (proton pump inhibitors); PAH-Pulmonary arterial hypertension confirmed by right heart catheterization. Immunomodulators includes Metothrexate, Leflunomide, Hydroxycloroquine; Azathioprine, Mycophenolate Mofetil and Cyclophosphamide; * Does not include sclerodactyly.

Figure 1.

Panel A - Survival in years from diagnosis of patients with SSc included in Reuma.pt in the first 2 years of disease (N=472). Panel B - survival according to SSc subset (lcSSc and dcSSC).

Disclosure of Interests:

None declared

Transferring Occlusal Anatomy from Worn Temporary Crowns to Zirconium Oxide Crowns

Purpose/Aim: To evaluate the accuracy of transferring the occlusal anatomy of provisional crowns to monolithic zirconium oxide crowns. Materials and Methods: From a prepared typodont-tooth (#36), ten CAD/CAM provisional polymethylethacrylate crowns were fabricated with the E4D system. Each provisional crown had its occlusion adjusted. They were scanned (E4D) and the .stl files of the crown preparations were merged with the files from the adjusted crowns (3 shape software) to produce ten polished monolithic zirconium oxide crowns. For comparison, provisional and monolithic zirconium oxide crowns were scanned (True-Definition scanner), the .stl files aligned, converted into a normalized 76x76-matrix, analyzed with ANOVA with repeated measures and Tukey's test. To generate deviation distribution tables and difference plots, .stl files (provisional crowns and monolithic zirconium oxide crowns) were merged with Geomagic software. Results: There were significant differences between provisional crowns and monolithic zirconium oxide crowns. The differences were manly in the fissure area. 86% of the calculated deviations were between + 0.06mm and - 0.04mm, 42.4% of all data points were within ± 0.022mm with a SD of 0.005mm. The main differences were in the fissures, requiring clinically none or only minimal occlusal adjustments for these zirconium oxide crowns.

NMRFinder: a novel method for 1D 1H-NMR metabolite annotation

INTRODUCTION

Methods for the automated and accurate identification of metabolites in 1D ¹H-NMR samples are crucial, but this is still an unsolved problem. Most available tools are mainly focused on metabolite quantification, thus limiting the number of metabolites that can be identified. Also, most only use reference spectra obtained under the same specific conditions of the target sample, limiting the use of available knowledge.

OBJECTIVES

The main goal of this work was to develop novel methods to perform metabolite annotation from 1D ¹H-NMR peaks with enhanced reliability, to aid the users in metabolite identification. An essential step was to construct a vast and up-do-date library of reference 1D ¹H-NMR peak lists collected under distinct experimental conditions.

METHODS

Three different algorithms were evaluated for their capacity to correctly annotate metabolites present in both synthetic and real samples and compared to publicly available tools. The best proposed method was evaluated in a plethora of scenarios, including missing references, missing peaks and peak shifts, to assess its annotation accuracy, precision and recall.

RESULTS

We gathered 1816 peak lists for 1387 different metabolites from several sources across different conditions for our reference library. A new method, NMRFinder, is proposed and allows matching 1D ¹H-NMR samples with all the reference peak lists in the library, regardless of acquisition conditions. Metabolites are scored according to the number of peaks matching the samples, how unique their peaks are in the library and how close the spectrum acquisition conditions are in relation to those of the samples. Results show a true positive rate of 0.984 when analysing computationally created samples, while 71.8% of the metabolites were annotated when analysing samples from previously identified public datasets.

CONCLUSION

NMRFinder performs metabolite annotation reliably and outperforms previous methods, being of great value in helping the user to ultimately identify metabolites. It is implemented in the R package specmine.

Transcontinental Dissemination of the L2b/D-Da Recombinant Chlamydia trachomatis Lymphogranuloma venereum (LGV) Strain: Need of Broad Multi-Country Molecular Surveillance

Previously, we identified a Chlamydia trachomatis lymphogranuloma venereum (LGV) recombinant strain possessing a non-LGV ompA genotype. Here, culture-independent genome sequencing confirms its circulation in Europe, Middle East, and North America, and unveils emergence of antibiotic resistance. Broad surveillance is needed.

MEWpy: A Computational Strain Optimization Workbench in Python

Summary

Metabolic Engineering aims to favour the overproduction of native, as well as non-native, metabolites by modifying or extending the cellular processes of a specific organism. In this context, Computational Strain Optimization (CSO) plays a relevant role by putting forward mathematical approaches able to identify potential metabolic modifications to achieve the defined production goals. We present MEWpy, a Python workbench for metabolic engineering, which covers a wide range of metabolic and regulatory modelling approaches, as well as phenotype simulation and CSO algorithms.

Availability and implementation

MEWpy can be installed from PyPi (pip install mewpy), the source code being available at https://github.com/BioSystemsUM/mewpy under the GPL license.

Causal integration of multi-omics data with prior knowledge to generate mechanistic hypotheses

Multi-omics datasets can provide molecular insights beyond the sum of individual omics. Various tools have been recently developed to integrate such datasets, but there are limited strategies to systematically extract mechanistic hypotheses from them. Here, we present COSMOS (Causal Oriented Search of Multi-Omics Space), a method that integrates phosphoproteomics, transcriptomics, and metabolomics datasets. COSMOS combines extensive prior knowledge of signaling, metabolic, and gene regulatory networks with computational methods to estimate activities of transcription factors and kinases as well as network-level causal reasoning. COSMOS provides mechanistic hypotheses for experimental observations across multi-omics datasets. We applied COSMOS to a dataset comprising transcriptomics, phosphoproteomics, and metabolomics data from healthy and cancerous tissue from eleven clear cell renal cell carcinoma (ccRCC) patients. COSMOS was able to capture relevant crosstalks within and between multiple omics layers, such as known ccRCC drug targets. We expect that our freely available method will be broadly useful to extract mechanistic insights from multi-omics studies.

Learnings from a decade experience of a community-based HIV and STI testing and counseling center in Lisbon – Portugal

Background

In the context of an increased number of men who have sex with men (MSM) being diagnosed with HIV infection in many European countries, it became a matter of maximum priority to consider new strategies to monitor and tackle the epidemic. In this scenario, CheckpointLX and a cohort study were projected as a sexual health and research center oriented towards MSM in Portugal.

Methods

In 2011 CheckpointLX was launched in Lisbon as a community-based center for anonymous and free rapid HIV and other sexually transmitted diseases (STI) testing with a strong component of counseling for sexual health, specially targeted at MSM. In the case of a reactive test, a medical appointment is proposed and scheduled. The Lisbon Cohort of MSM is an ongoing observational prospective study conducted at CheckpointLX. Collected data include sexual behaviors, preventive strategies, and history of STI.

Results

Until July 2019, 7,351 HIV-negative MSM chose to participate in the Lisbon Cohort of MSM. 3,523 had at least one follow-up visit. The median age was 29 (IQR 25 - 37), and 27% were born in a foreign country, including 15% born in Africa and South America. HIV incidence increased up until 2015, reaching 5 reactive tests per 100 tested annually. There has been a sustained decrease in HIV observed since 2015. The use of HIV prevention tools was provided: 31% used condoms consistently, 3% reported PrEP, and 4% PEP.

Conclusions

A decade since the beginning of this experience shows positive results, such as increased access and testing. We promoted a stigma-free service that facilitated MSM's and other key population's access to sexual health care. We contribute unique data for assisting in the monitoring of the Dublin Declaration in Portugal.

Early ART in Acute HIV-1 Infection: Impact on the B-Cell Compartment

HIV-1 infection induces B cell defects, not fully recovered upon antiretroviral therapy (ART). Acute infection and the early start of ART provide unique settings to address the impact of HIV on the B cell compartment. We took advantage of a cohort of 21 seroconverters, grouped according to the presence of severe manifestations likely mediated by antibodies or immune complexes, such as Guillain-Barré syndrome and autoimmune thrombocytopenic purpura, with a follow-up of 8 weeks upon effective ART. We combined B and T cell phenotyping with serum immunoglobulin level measurement and quantification of sj-KRECs and ΔB to estimate bone marrow output and peripheral proliferative history of B cells, respectively. We observed marked B cell disturbances, notably a significant expansion of cells expressing low levels of CD21, in parallel with markers of both impaired bone marrow output and increased peripheral B cell proliferation. This B cell dysregulation is likely to contribute to the severe immune-mediated conditions, as attested by the higher serum IgG and the reduced levels of sj-KRECs with increased ΔB in these individuals as compared to those patients with mild disease. Nevertheless, upon starting ART, the dynamic of B cell recovery was not distinct in the two groups, featuring both persistent alterations by week 8. Overall, we showed for the first time that acute HIV-1 infection is associated with decreased bone marrow B cell output assessed by sj-KRECs. Our study emphasizes the need to intervene in both bone marrow and peripheral responses to facilitate B cell recovery during acute HIV-1 infection.

Predicting promoters in phage genomes using PhagePromoter

SUMMARY

The growing interest in phages as antibacterial agents has led to an increase in the number of sequenced phage genomes, increasing the need for intuitive bioinformatics tools for performing genome annotation. The identification of phage promoters is indeed the most difficult step of this process. Due to the lack of online tools for phage promoter prediction, we developed PhagePromoter, a tool for locating promoters in phage genomes, using machine learning methods. This is the first online tool for predicting promoters that uses phage promoter data and the first to identify both host and phage promoters with different motifs.

AVAILABILITY AND IMPLEMENTATION

This tool was integrated in the Galaxy framework and it is available online at: https://bit.ly/2Dfebfv.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.