Perspectives and Challenges in Microbial Communities Metabolic Modeling

Bacteria have evolved to efficiently interact each other, forming complex entities known as microbial communities. These “super-organisms” play a central role in maintaining the health of their eukaryotic hosts and in the cycling of elements like carbon and nitrogen. However, despite their crucial importance, the mechanisms that influence the functioning of microbial communities and their relationship with environmental perturbations are obscure. The study of microbial communities was boosted by tremendous advances in sequencing technologies, and in particular by the possibility to determine genomic sequences of bacteria directly from environmental samples. Indeed, with the advent of metagenomics, it has become possible to investigate, on a previously unparalleled scale, the taxonomical composition and the functional genetic elements present in a specific community. Notwithstanding, the metagenomic approach per se suffers some limitations, among which the impossibility of modeling molecular-level (e.g., metabolic) interactions occurring between community members, as well as their effects on the overall stability of the entire system. The family of constraint-based methods, such as flux balance analysis, has been fruitfully used to translate genome sequences in predictive, genome-scale modeling platforms. Although these techniques have been initially developed for analyzing single, well-known model organisms, their recent improvements allowed engaging in multi-organism in silico analyses characterized by a considerable predictive capability. In the face of these advances, here we focus on providing an overview of the possibilities and challenges related to the modeling of metabolic interactions within a bacterial community, discussing the feasibility and the perspectives of this kind of analysis in the (near) future

Modelling microbial metabolic rewiring during growth in a complex medium

BACKGROUND: In their natural environment, bacteria face a wide range of environmental conditions that change over time and that impose continuous rearrangements at all the cellular levels (e.g. gene expression, metabolism). When facing a nutritionally rich environment, for example, microbes first use the preferred compound(s) and only later start metabolizing the other one(s). A systemic re-organization of the overall microbial metabolic network in response to a variation in the composition/concentration of the surrounding nutrients has been suggested, although the range and the entity of such modifications in organisms other than a few model microbes has been scarcely described up to now. RESULTS: We used multi-step constraint-based metabolic modelling to simulate the growth in a complex medium over several time steps of the Antarctic model organism Pseudoalteromonas haloplanktis TAC125. As each of these phases is characterized by a specific set of amino acids to be used as carbon and energy source our modelling framework describes the major consequences of nutrients switching at the system level. The model predicts that a deep metabolic reprogramming might be required to achieve optimal biomass production in different stages of growth (different medium composition), with at least half of the cellular metabolic network involved (more than 50% of the metabolic genes). Additionally, we show that our modelling framework is able to capture metabolic functional association and/or common regulatory features of the genes embedded in our reconstruction (e.g. the presence of common regulatory motifs). Finally, to explore the possibility of a sub-optimal biomass objective function (i.e. that cells use resources in alternative metabolic processes at the expense of optimal growth) we have implemented a MOMA-based approach (called nutritional-MOMA) and compared the outcomes with those obtained with Flux Balance Analysis (FBA). Growth simulations under this scenario revealed the deep impact of choosing among alternative objective functions on the resulting predictions of fluxes distribution. CONCLUSIONS: Here we provide a time-resolved, systems-level scheme of PhTAC125 metabolic re-wiring as a consequence of carbon source switching in a nutritionally complex medium. Our analyses suggest the presence of a potential efficient metabolic reprogramming machinery to continuously and promptly adapt to this nutritionally changing environment, consistent with adaptation to fast growth in a fairly, but probably inconstant and highly competitive, environment. Also, we show i) how functional partnership and co-regulation features can be predicted by integrating multi-step constraint-based metabolic modelling with fed-batch growth data and ii) that performing simulations under a sub-optimal objective function may lead to different flux distributions in respect to canonical FBA. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-016-3311-0) contains supplementary material, which is available to authorized users

Defective FoxP3+ Treg cell differentiation in the gut of Type 1 Diabetic patients

Environmental factors that act at the intestinal level such as diet, drugs, and microflora have a high impact on the pathogenesis of autoimmune Type 1 Diabetes (T1D), but it is still unclear how the gut milieu affects autoimmunity outside the intestine. Here we show that peripheral FoxP3+ Treg cell differentiation, a mechanism that takes place in the gut and is crucial to maintain systemic immune tolerance, is impaired in T1D patients. These results provide the first evidence that gut mucosa alteration could predispose to autoimmune T1D by affecting systemic immune regulation

Constraint-based modeling identifies new putative targets to fight colistin-resistant A. baumannii infections

Acinetobacter baumannii is a clinical threat to human health, causing major infection outbreaks worldwide. As new drugs against Gram-negative bacteria do not seem to be forthcoming, and due to the microbial capability of acquiring multi-resistance, there is an urgent need for novel therapeutic targets. Here we have derived a list of new potential targets by means of metabolic reconstruction and modelling of A. baumannii ATCC 19606. By integrating constraint-based modelling with gene expression data, we simulated microbial growth in normal and stressful conditions (i.e. following antibiotic exposure). This allowed us to describe the metabolic reprogramming that occurs in this bacterium when treated with colistin (the currently adopted last-line treatment) and identify a set of genes that are primary targets for developing new drugs against A. baumannii, including colistin-resistant strains. It can be anticipated that the metabolic model presented herein will represent a solid and reliable resource for the future treatment of A. baumannii infections

Role of high dose octreotide LAR for the treatment of GEP-NETs

Neuroendocrine Tumours (NETs) are a heterogeneous group of rare neoplasms that account for 0,5% of all malignancies. The increased incidence observed in the last few decades may be accounted for by increased awareness, improved diagnostic tools and a revision in the definition. The main primary sites are the gastro-entero-pancreatic (GEP) tract (62-67%), and the lung (22-27%). In patients with GEP-NETs, the strongest predictor of 5-years survival is the staging. An adequate clinical management of GEP-NETs should be multidisciplinary and should aim at assuring a good quality of life. Somatostatin (sst) analogues are widely used in these tumours, which often express sst receptors, since they are demonstrated to reduce clinical symptoms and tumour growth. Herein we explore the usefulness of doubling octreotide LAR dose in selected patients after escaping from symptoms control and/or tumour stabilization in course of treatment with standard dose

Autoantibody Response to Islet Transplantation in Type 1 Diabetes

Islet allotransplantation into patients with autoimmune type 1 diabetes represents a reexposure to autoantigen. Here, measurement of antibodies to GAD and IA-2 autoantigens before and after islet transplantation in 36 patients (33 receiving islet plus kidney grafts with cyclosporin and steroid-based immunosuppression, and 3 receiving solitary islet transplants with mycophenolate but cyclosporin-free immunosuppression) demonstrated marked rises in GAD antibodies within 7 days posttransplantation in 5 patients (3 receiving islet after kidney transplants, and 2 receiving solitary islet transplants) and within 30 days in the third patient receiving solitary islet transplantation. GAD antibodies were of the IgG1 subclass, against major autoantigenic epitopes, and in cases of islet after kidney transplants, the responses were short-lived and not accompanied by HLA antibodies. Two of these patients had subsequent marked rises of IA-2 antibodies, and an additional patient had a marked rise in IgM-GAD antibodies 3 years after transplantation. Insulin independence was not achieved in patients with autoantibody elevations and was significantly less frequent in these patients. These data are consistent with a reactivation of autoimmunity that may be dependent on immunosuppression therapy and is associated with impaired graft function

The Burden of Structured Self-Monitoring of Blood Glucose on Diabetes-Specific Quality of Life and Locus of Control in Patients with Noninsulin-Treated Type 2 Diabetes: The PRISMA Study

Background: To evaluate whether structured self-monitoring of blood glucose (SMBG) is associated with changes in diabetes-specific quality of life (DSQoL) and locus of control (LOC) in patients with noninsulin-treated type 2 diabetes (T2DM). Study Design and Methods: In this analysis of the PRISMA (Prospective Randomized Trial on Intensive SMBG Management Added Value in Noninsulin-Treated T2DM Patients) Study psychosocial data, we evaluated the impact of 12 months of structured SMBG on the individual domains of DSQoL and LOC questionnaires, including the role of selected confounders. Results: The score for Satisfaction, Impact, and Worry domains (DSQoL) improved when compared with baseline, without significant differences between structured SMBG regimen (intervention group, n = 501) and active control group (n = 523). Scores for Internal, Chance, and Powerful Others domains (LOC) improved compared with baseline, with a significant between-group change in Chance (P = 0.0309). For DSQoL domain score, improvements were associated with higher number of SMBG measurements (P = 0.007), older age (P = 0.013), and male sex (P = 0.0133) for Satisfaction and with male sex (P < 0.0001) for Worry. Concerning LOC domain score, improvements were associated with longer diabetes duration (P = 0.0084) and younger age (P < 0.0001) for Chance and total number of SMBG measurements (P = 0.0036) for Internal, with the intervention group close to being significant (P = 0.06). Conclusions: Our analysis demonstrates that in patients with noninsulin-treated T2DM, structured SMBG is not associated with a deterioration of quality of life and LOC, which is strongly predicted by demographics and diabetes-related variables. These findings should be considered when tailoring educational support to SMBG for these patients

Post hoc analysis of a randomized, double-blind, prospective trial evaluating a CXCR1/2 inhibitor in new-onset type 1 diabetes: endo-metabolic features at baseline identify a subgroup of responders

AimIn a recent randomized, multicenter trial (NCT02814838) a short-term anti-inflammatory treatment with ladarixin (LDX; an inhibitor of the CXCR1/2 chemokine receptors) did not show benefit on preserving residual beta cell function in new-onset type 1 diabetes. We present a post hoc analysis of trial patients in the predefined subgroup analysis developed according to baseline daily insulin requirement (DIR) tertiles.MethodA double-blind, randomized (2:1), placebo-controlled study was conducted in 45 men and 31 women (aged 18–46 years) within 100 days of the first insulin administration. Patients received LDX (400 mg twice daily) for three cycles of 14 days on/14 days off, or placebo. The primary endpoint was the area under the curve for C-peptide [AUC (0–120 min)] in response to a 2-h mixed meal tolerance test (MMTT) at week 13 ± 1. Seventy-five patients completed the week 13 MMTT and were divided into three groups according to the DIR tertiles: lower, ≤ 0.23U/kg/die (n = 25); middle, 0.24–0.40 U/kg/die (n = 24); upper, ≥ 0.41 U/kg/die (n = 26).ResultsWhen considering the patients in the upper tertile (HIGH-DIR), C-peptide AUC (0–120 min) at 13 weeks was higher in the LDX group (n = 16) than in the placebo (n = 10) group [difference: 0.72 nmol/L (95% CI 0.9–1.34), p = 0.027]. This difference reduced over time (0.71 nmol/L at 26 weeks, p = 0.04; 0.42 nmol/L at 52 weeks, p = 0.29), while it has never been significant at any time in patients in the lower and/or middle tertile (LOW-DIR). We characterized at baseline the HIGH-DIR and found that endo-metabolic (HOMA-B, adiponectin, and glucagon-to-C-peptide ratio) and immunologic (chemokine (C-C motif) ligand 2 (CCL2)/monocyte chemoattractant protein 1 (MCP1) and Vascular Endothelial Growth Factor (VEGF)) features distinguished this group from LOW-DIR.ConclusionWhile LDX did not prevent the progressive loss of beta-cell function in the majority of treated subjects, the post hoc analysis suggests that it could work in subjects with HIGH-DIR at baseline. As we found differences in endo-metabolic and immunologic parameters within this subgroup, this generates the hypothesis that the interactions between host factors and drug action can contribute to its efficacy. Further research is needed to evaluate this hypothesis

Consensus recommendations for the use of Ambulatory Glucose Profile in clinical practice

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Co-Graft of Allogeneic Immune Regulatory Neural Stem Cells (NPC) and Pancreatic Islets Mediates Tolerance, while Inducing NPC-Derived Tumors in Mice

Data available on the immunomodulatory properties of neural stem/precursor cells (NPC) support their possible use as modulators for immune-mediated process. The aim of this study was to define whether NPC administered in combination with pancreatic islets prevents rejection in a fully mismatched allograft model.Diabetic Balb/c mice were co-transplanted under the kidney capsule with pancreatic islets and GFP(+) NPC from fully mismatched C57BL/6 mice. The following 4 groups of recipients were used: mice receiving islets alone; mice receiving islets alone and treated with standard immunosuppression (IL-2Ralpha chain mAbs + FK506 + Rapamycin); mice receiving a mixed islet/NPC graft under the same kidney capsule (Co-NPC-Tx); mice receiving the islet graft under the left kidney capsule and the NPC graft under the right kidney capsule (NPC-Tx). Our results demonstrate that only the co-transplantation and co-localization of NPC and islets (Co-NPC-Tx) induce stable long-term graft function in the absence of immunosuppression. This condition is associated with an expansion of CD4(+)CD25(+)FoxP3(+) T regulatory cells in the spleen. Unfortunately, stable graft function was accompanied by constant and reproducible development of NPC-derived cancer mainly sustained by insulin secretion.These data demonstrate that the use of NPC in combination with islets prevents graft rejection in a fully mismatched model. However, the development of NPC-derived cancer raises serious doubts about the safety of using adult stem cells in combination with insulin-producing cells outside the original microenvironment