Combined mechanistic modeling and machine-learning approaches in systems biology - A systematic literature review

Background and objective: Mechanistic-based Model simulations (MM) are an effective approach commonly employed, for research and learning purposes, to better investigate and understand the inherent behavior of biological systems. Recent advancements in modern technologies and the large availability of omics data allowed the application of Machine Learning (ML) techniques to different research fields, including systems biology. However, the availability of information regarding the analyzed biological context, sufficient experimental data, as well as the degree of computational complexity, represent some of the issues that both MMs and ML techniques could present individually. For this reason, recently, several studies suggest overcoming or significantly reducing these drawbacks by combining the above-mentioned two methods. In the wake of the growing interest in this hybrid analysis approach, with the present review, we want to systematically investigate the studies available in the scientific literature in which both MMs and ML have been combined to explain biological processes at genomics, proteomics, and metabolomics levels, or the behavior of entire cellular populations. Methods: Elsevier Scopus®, Clarivate Web of Science™ and National Library of Medicine PubMed® databases were enquired using the queries reported in Table 1, resulting in 350 scientific articles. Results: Only 14 of the 350 documents returned by the comprehensive search conducted on the three major online databases met our search criteria, i.e. present a hybrid approach consisting of the synergistic combination of MMs and ML to treat a particular aspect of systems biology. Conclusions: Despite the recent interest in this methodology, from a careful analysis of the selected papers, it emerged how examples of integration between MMs and ML are already present in systems biology, highlighting the great potential of this hybrid approach to both at micro and macro biological scales

Forensic Proteomics for the Evaluation of the post-Mortem Decay in Bones

Current methods for the evaluation of post-mortem interval (PMI) of skeletal remains suffer from poor accuracy, due to the great number of variables that affect the diagenetic process and to the lack of specific guidelines to address this issue. During decomposition, proteins can undergo cumulative decay over the time, resulting in a decrease in the range and abundance of proteins present (i.e., the proteome) in different tissues as well as in an increase of post-translational modifications occurring on these proteins. In this study, we evaluate the applicability of bone proteomic analyses to simulated forensic contexts, looking for specific biomarkers that may help the estimation of PMI and evaluating a previously discovered marker for the estimation of biological age. We noticed a reduction of specific plasma and muscle proteins with increasing PMIs, as well as an increased deamidation of biglycan, a protein with a role in modulating bone growth and mineralization, which may be developed further for the estimation of PMI from a molecular perspective. We also corroborated our previous results regarding the use of fetuin-A as a potential biomarker for the estimation of age-at-death, demonstrating the applicability and the great potential that proteomics may have towards forensic sciences. Significance: The estimation of the post-mortem interval has a key role in forensic investigations, however nowadays it still suffers from poor reliability, especially when bodies are heavily decomposed. Here we proposed for the first time the application of bone proteomics to the estimation of the time elapsed from death, and we found some new potential biomarkers to address this specific question. This study hence proves the applicability of proteomic analyses to forensic sciences, showing that proteomics may become an integrant discipline to answer unresolved forensic issues

Bone Diagenesis in Short Timescales: Insights from an Exploratory Proteomic Analysis

The evaluation of bone diagenetic phenomena in archaeological timescales has a long history; however, little is known about the origins of the microbes driving bone diagenesis, nor about the extent of bone diagenesis in short timeframes—such as in forensic contexts. Previously, the analysis of non-collagenous proteins (NCPs) through bottom-up proteomics revealed the presence of potential biomarkers useful in estimating the post-mortem interval (PMI). However, there is still a great need for enhancing the understanding of the diagenetic processes taking place in forensic timeframes, and to clarify whether proteomic analyses can help to develop better models for estimating PMI reliably. To address these knowledge gaps, we designed an experiment based on whole rat carcasses, defleshed long rat bones, and excised but still-fleshed rat limbs, which were either buried in soil or exposed on a clean plastic surface, left to decompose for 28 weeks, and retrieved at different time intervals. This study aimed to assess differences in bone protein relative abundances for the various deposition modalities and intervals. We further evaluated the effects that extrinsic factors, autolysis, and gut and soil bacteria had on bone diagenesis via bottom-up proteomics. Results showed six proteins whose abundance was significantly different between samples subjected to either microbial decomposition (gut or soil bacteria) or to environmental factors. In particular, muscle- and calcium-binding proteins were found to be more prone to degradation by bacterial attack, whereas plasma and bone marrow proteins were more susceptible to exposure to extrinsic agents. Our results suggest that both gut and soil bacteria play key roles in bone diagenesis and protein decay in relatively short timescales, and that bone proteomics is a proficient resource with which to identify microbially-driven versus extrinsically-driven diagenesis

Analysis of a Cardiac-Necrosis-Biomarker Release in Patients with Acute Myocardial Infarction via Nonlinear Mixed-Effects Models

The release of the cardiac troponin T (cTnT) in patients with acute myocardial infarc tion (AMI) has been analyzed through a methodology based on nonlinear mixed-effects (NME) models. The aim of this work concerns the investigation of any possible relationship between clin ical covariates and the dynamics of the release of cTnT to derive more detailed and useful clinical information for the correct treatment of these patients. An ad-hoc mechanistic model describing the biomarker release process after AMI has been devised, assessed, and exploited to evaluate the im pact of the available clinical covariates on the cTnT release dynamic. The following approach was tested on a preliminary dataset composed of a small number of potential clinical covariates: em ploying an unsupervised approach, and despite the limited sample size, dyslipidemia, a known risk factor for cardiovascular disease, was found to be a statistically significant covariate. By increasing the number of covariates considered in the model, and patient cohort, we envisage that this approach may provide an effective means to automatically classify AMI patients and to investigate the role of interactions between clinical covariates and cTnT relea

Selectivity of the CUBAN domain in the recognition of ubiquitin and NEDD8

Among the members of the Ubiquitin‐like (Ubl) protein family, Neural precursor cell expressed developmentally down‐regulated protein 8 (NEDD8) is the closest in sequence to ubiquitin (57% identity). The two modification mechanisms and their functions, however, are highly distinct and the two Ubls are not interchangeable. A complex network of interactions between modifying enzymes and adaptors, most of which are specific while others are promiscuous, ensures selectivity. Many domains that bind the ubiquitin hydrophobic patch also bind NEDD8 while no domain that specifically binds NEDD8 has yet been described. Here we report an unbiased selection of domains that bind ubiquitin and/or NEDD8 and we characterize their specificity/promiscuity. Many ubiquitin binding domains bind ubiquitin preferentially and, to a lesser extent, NEDD8. In a few cases, the affinity of these domains for NEDD8 can be increased by substituting the alanine at position 72 with arginine, as in ubiquitin. We have also identified a unique domain, mapping to the carboxyl‐end of the protein KHNYN, which has a starkly preference for NEDD8. Given its ability to bind neddylated cullins we have named this domain CUBAN (Cullin Binding domain Associating with NEDD8). We present here the solution structure of the CUBAN domain both in the isolated form and in complex with NEDD8. The results contribute to the understanding of the discrimination mechanism between ubiquitin and the Ubl. They also provide new insights on the biological role of a ill‐defined protein, whose function is hitherto only predicted

Clinical efficacy of Enzyme Replacement Therapy in paediatric Hunter patients, an independent study of 3.5 years

BACKGROUND: Hunter Syndrome is an X-linked lysosomal storage disorder due to the deficit of iduronate 2-sulfatase, an enzyme catalysing the degradation of the glycosaminoglycans (GAG) dermatan- and heparan-sulfate. Treatment of the disease is mainly performed by Enzyme Replacement Therapy (ERT) with idursulfase, in use since 2006. Clinical efficacy of ERT has been monitored mainly by the Hunter Outcome Survey (HOS) while very few independent studies have been so far conducted. The present study is a 3.5-years independent follow-up of 27 Hunter patients, starting ERT between 1.6 and 27 years of age, with the primary aim to evaluate efficacy of the therapy started at an early age (<12 years). METHODS: In this study, we evaluated: urinary GAG content, hepato/splenomegaly, heart valvulopathies, otorinolaryngological symptoms, joint range of motion, growth, distance covered in the 6-minute walk test, neurological involvement. For data analysis, the 27 patients were divided into three groups according to the age at start of ERT: ≤5 years, >5 and ≤ 12 years and > 12 years. Patients were analysed both as 3 separate groups and also as one group; in addition, the 20 patients who started ERT up to 12 years of age were analysed as one group. Finally, patients presenting a “severe” phenotype were compared with “attenuated” ones. RESULTS: Data analysis revealed a statistically significant reduction of the urinary GAG in patients ≤5 years and ≤ 12 years and of the hepatomegaly in the group aged >5 and ≤ 12 years. Although other clinical signs improved in some of the patients monitored, statistical analysis of their variation did not reveal any significant changes following enzyme administration. The evaluation of ERT efficacy in relation to the severity of the disease evidenced slightly higher improvements as for hepatomegaly, splenomegaly, otological disorders and adenotonsillar hypertrophy in severe vs attenuated patients. CONCLUSIONS: Although the present protocol of idursulfase administration may result efficacious in delaying the MPS II somatic disease progression at some extent, in this study we observed that several signs and symptoms did not improve during the therapy. Therefore, a strict monitoring of the efficacy obtained in the patients under ERT is becoming mandatory for clinical, ethical and economic reasons. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13023-014-0129-1) contains supplementary material, which is available to authorized users

Prognostic value of soluble ST2, high-sensitivity cardiac troponin, and NT-proBNP in type 2 diabetes: a 15-year retrospective study

Background: Patients with type 2 diabetes (T2DM) present an increased risk of cardiovascular (CV) disease and excess CV-related mortality. Beyond the established role of brain natriuretic peptide (BNP) and cardiac troponins (cTn), other non-cardiac-specific biomarkers are emerging as predictors of CV outcomes in T2DM. Methods: Serum levels of soluble suppression of tumorigenesis 2 (sST2), high-sensitivity (hs)-cTnI, and N-terminal (NT)-proBNP were assessed in 568 patients with T2DM and 115 healthy controls (CTR). Their association with all-cause mortality and the development of diabetic complications was tested in T2DM patients over a median follow-up of 16.8 years using Cox models and logistic regressions. Results: sST2 followed an increasing trend from CTR to uncomplicated T2DM patients (T2DM-NC) to patients with at least one complication (T2DM-C), while hs-cTnI was significantly higher in T2DM-C compared to CTR but not to T2DM-NC. A graded association was found between sST2 (HR 2.76 [95% CI 1.20-6.33] for ≥ 32.0 ng/mL and 2.00 [1.02-3.94] for 16.5-32.0 ng/mL compared to &lt; 16.5 ng/mL, C-statistic = 0.729), NT-proBNP (HR 2.04 [1.90-4.55] for ≥ 337 ng/L and 1.48 [1.05-2.10] for 89-337 ng/L compared to &lt; 89 ng/L, C-statistic = 0.741), and 15-year mortality in T2DM, whereas increased mortality was observed in patients with hs-cTnI ≥ 7.8 ng/L (HR 1.63 [1.01-2.62]). A 'cardiac score' based on the combination of sST2, hs-cTnI, and NT-proBNP was significantly associated with all-cause mortality (HR 1.35 [1.19-1.53], C-statistic = 0.739) and development of CV events. Conclusions: sST2, hs-cTnI, and NT-proBNP are associated with 15-year mortality and onset of CV events in T2DM. The long-term prognostic value of sST2 and its ability to track variables related to insulin resistance and associated metabolic disorders support its implementation into routine clinical practice

Soil Fungal Communities Investigated by Metabarcoding Within Simulated Forensic Burial Contexts

Decomposition of animal bodies in the burial environment plays a key role in the biochemistry of the soil, altering the balance of the local microbial populations present before the introduction of the carcass. Despite the growing number of studies on decomposition and soil bacterial populations, less is known on its effects on fungal communities. Shifts in the fungal populations at different post-mortem intervals (PMIs) could provide insights for PMI estimation and clarify the role that specific fungal taxa have at specific decomposition stages. In this study, we buried pig carcasses over a period of 1- to 6-months, and we sampled the soil in contact with each carcass at different PMIs. We performed metabarcoding analysis of the mycobiome targeting both the internal transcribed spacer (ITS) 1 and 2, to elucidate which one was more suitable for this purpose. Our results showed a decrease in the fungal taxonomic richness associated with increasing PMIs, and the alteration of the soil fungal signature even after 6 months post-burial, showing the inability of soil communities to restore their original composition within this timeframe. The results highlighted taxonomic trends associated with specific PMIs, such as the increase of the Mortierellomycota after 4- and 6-months and of Ascomycota particularly after 2 months, and the decrease of Basidiomycota from the first to the last time point. We have found a limited number of taxa specifically associated with the carrion and not present in the control soil, showing that the major contributors to the recorded changes are originated from the soil and were not introduced by the carrion. As this is the first study conducted on burial graves, it sets the baseline for additional studies to investigate the role of fungal communities on prolonged decomposition periods and to identify fungal biomarkers to improve the accuracy of PMI prediction for forensic applications

Successive Bacterial Colonisation of Pork and its Implications for Forensic Investigations

Aims: Bacteria are considered one of the major driving forces of the mammalian decomposition process and have only recently been recognised as forensic tools. At this point, little is known about their potential use as ‘post-mortem clocks’. This study aimed to establish the proof of concept for using bacterial identification as post-mortem interval (PMI) indicators, using a multi-omics approach. Methods and Results: Pieces of pork were placed in the University’s outdoor facility and surface swabs were taken at regular intervals up to 60 days. Terminal restriction fragment length polymorphism (T-RFLP) of the 16S rDNA was used to identify bacterial taxa. It succeeded in detecting two out of three key contributors involved in decomposition and represents the first study to reveal Vibrionaceae as abundant on decomposing pork. However, a high fraction of present bacterial taxa could not be identified by T-RFLP. Proteomic analyses were also performed at selected time points, and they partially succeeded in the identification of precise strains, subspecies and species of bacteria that colonized the body after different PMIs. Conclusion: T-RFLP is incapable of reliably and fully identifying bacterial taxa, whereas proteomics could help in the identification of specific strains of bacteria. Nevertheless, microbial identification by next generation sequencing might be used as PMI clock in future investigations and in conjunction with information provided by forensic entomologists. Significance and Impact of the Study: To the best of our knowledge, this work represents the first attempt to find a cheaper and easily accessible, culture-independent alternative to high-throughput techniques to establish a ‘microbial clock’, in combination with proteomic strategies to address this issue