Background
Cancer cachexia is characterized by a negative energy balance, muscle and adipose tissue wasting, insulin resistance, and systemic inflammation. Because of its strong negative impact on ...prognosis and its multifactorial nature that is still not fully understood, cachexia remains an important challenge in the field of cancer treatment. Recent animal studies indicate that the gut microbiota is involved in the pathogenesis and manifestation of cancer cachexia, but human data are lacking. The present study investigates gut microbiota composition, short‐chain fatty acids (SCFA), and inflammatory parameters in human cancer cachexia.
Methods
Faecal samples were prospectively collected in patients (N = 107) with pancreatic cancer, lung cancer, breast cancer, or ovarian cancer. Household partners (N = 76) of the patients were included as healthy controls with similar diet and environmental conditions. Patients were classified as cachectic if they lost >5% body weight in the last 6 months. Gut microbiota composition was analysed by sequencing of the 16S rRNA V4 gene region. Faecal SCFA levels were quantified by gas chromatography. Faecal calprotectin was assessed with enzyme‐linked immunosorbent assay. Serum C‐reactive protein and leucocyte counts were retrieved from medical records.
Results
Cachexia prevalence was highest in pancreatic cancer (66.7%), followed by ovarian cancer (25%), lung cancer (20.8%), and breast cancer (17.3%). Microbial α‐diversity was not significantly different between cachectic cancer patients (N = 33), non‐cachectic cancer patients (N = 74), or healthy controls (N = 76) (species richness P = 0.31; Shannon effective index P = 0.46). Community structure (β‐diversity) tended to differ between these groups (P = 0.053), although overall differences were subtle and no clear clustering of samples was observed. Proteobacteria (P < 0.001), an unknown genus from the Enterobacteriaceae family (P < 0.01), and Veillonella (P < 0.001) were more abundant among cachectic cancer patients. Megamonas (P < 0.05) and Peptococcus (P < 0.001) also showed differential abundance. Faecal levels of all SCFA tended to be lower in cachectic cancer patients, but only acetate concentrations were significantly reduced (P < 0.05). Faecal calprotectin levels were positively correlated with the abundance of Peptococcus, unknown Enterobacteriaceae, and Veillonella. We also identified several correlations and interactions between clinical and microbial parameters.
Conclusions
This clinical study provided the first insights into the alterations of gut microbiota composition and SCFA levels that occur in cachectic cancer patients and how they are related to inflammatory parameters. These results pave the way for further research examining the role of the gut microbiota in cancer cachexia and its potential use as therapeutic target.
Intestinal ischemia-reperfusion (IR) injury is associated with high mortality rates, which have not improved in the past decades despite advanced insight in its pathophysiology using in vivo animal ...and human models. The inability to translate previous findings to effective therapies emphasizes the need for a physiologically relevant in vitro model to thoroughly investigate mechanisms of IR-induced epithelial injury and test potential therapies. In this study, we demonstrate the use of human small intestinal organoids to model IR injury by exposing organoids to hypoxia and reoxygenation (HR). A mass-spectrometry-based proteomics approach was applied to characterize organoid differentiation and decipher protein dynamics and molecular mechanisms of IR injury in crypt-like and villus-like human intestinal organoids. We showed successful separation of organoids exhibiting a crypt-like proliferative phenotype, and organoids exhibiting a villus-like phenotype, enriched for enterocytes and goblet cells. Functional enrichment analysis of significantly changing proteins during HR revealed that processes related to mitochondrial metabolism and organization, other metabolic processes, and the immune response were altered in both organoid phenotypes. Changes in protein metabolism, as well as mitophagy pathway and protection against oxidative stress were more pronounced in crypt-like organoids, whereas cellular stress and cell death associated protein changes were more pronounced in villus-like organoids. Profile analysis highlighted several interesting proteins showing a consistent temporal profile during HR in organoids from different origin, such as NDRG1, SDF4 or DMBT1. This study demonstrates that the HR response in human intestinal organoids recapitulates properties of the in vivo IR response. Our findings provide a framework for further investigations to elucidate underlying mechanisms of IR injury in crypt and/or villus separately, and a model to test therapeutics to prevent IR injury.
Identification of optimal genetic manipulation strategies for redirecting substrate uptake towards a desired product is a challenging task owing to the complexity of metabolic networks, esp. in terms ...of large number of routes leading to the desired product. Algorithms that can exploit the whole range of optimal and suboptimal routes for product formation while respecting the biological objective of the cell are therefore much needed. Towards addressing this need, we here introduce the notion of structural flux, which is derived from the enumeration of all pathways in the metabolic network in question and accounts for the contribution towards a given biological objective function. We show that the theoretically estimated structural fluxes are good predictors of experimentally measured intra-cellular fluxes in two model organisms, namely, Escherichia coli and Saccharomyces cerevisiae. For a small number of fluxes for which the predictions were poor, the corresponding enzyme-coding transcripts were also found to be distinctly regulated, showing the ability of structural fluxes in capturing the underlying regulatory principles. Exploiting the observed correspondence between in vivo fluxes and structural fluxes, we propose an in silico metabolic engineering approach, iStruF, which enables the identification of gene deletion strategies that couple the cellular biological objective with the product flux while considering optimal as well as sub-optimal routes and their efficiency.
This study investigated whether there are differences in the composition of the cutaneous microbiome of the unaffected skin between patients with pressure ulcers compared with those without pressure ...ulcers. The cutaneous microbiome of the unaffected skin of 15 patients with sacral pressure ulcers compared to 15 patients without pressure ulcers was analysed. It demonstrated that the inter-individual variation in skin microbiota of patients with pressure ulcers was significantly higher (P = 0.01). The abundance of 23 species was significantly different with Staphylococcus aureus and unclassified Enterococcus the most abundant species in patients with pressure ulcers. Random Forest models showed that eight species were associated with pressure ulcers occurrence in 81% of the patients. A subset of four species gave the strongest interaction. The presence of unclassified Enterococcus had the highest association with pressure ulcer occurrence. This study is the first to demonstrate that the cutaneous microbiome is altered in patients with pressure ulcers.
The microenvironment of solid tumors is a key determinant of therapy efficacy. The co-occurrence of oxygen and nutrient deprivation is a common phenomenon of the tumor microenvironment and associated ...with treatment resistance. Cholangiocarcinoma (CCA) is characterized by a very poor prognosis and pronounced chemoresistance. A better understanding of the underlying molecular mechanisms is urgently needed to improve therapy strategies against CCA. We sought to investigate the importance of the conditionally essential amino acid glutamine, a centrally important nutrient for a variety of solid tumors, for CCA. Glutamine levels were strongly decreased in CCA samples and the growth of established human CCA cell lines was highly dependent on glutamine. Using gradual reduction of external glutamine, we generated derivatives of CCA cell lines which were able to grow without external glutamine (termed glutamine-depleted (GD)). To analyze the effects of coincident oxygen and glutamine deprivation, GD cells were treated with cisplatin or gemcitabine under normoxia and hypoxia. Strikingly, the well-established phenomenon of hypoxia-induced chemoresistance was completely reversed in GD cells. In order to better understand the underlying mechanisms, we focused on the oncogene c-Myc. The combination of cisplatin and hypoxia led to sustained c-Myc protein expression in wildtype cells. In contrast, c-Myc expression was reduced in response to the combinatorial treatment in GD cells, suggesting a functional importance of c-Myc in the process of hypoxia-induced chemoresistance. In summary, these findings indicate that the mechanisms driving adaption to tumor microenvironmental changes and their relevance for the response to therapy are more complex than expected.
The description of a metabolic network in terms of elementary (flux) modes (EMs) provides an important framework for metabolic pathway analysis. However, their application to large networks has been ...hampered by the combinatorial explosion in the number of modes. In this work, we develop a method for generating random samples of EMs without computing the whole set.
Our algorithm is an adaptation of the canonical basis approach, where we add an additional filtering step which, at each iteration, selects a random subset of the new combinations of modes. In order to obtain an unbiased sample, all candidates are assigned the same probability of getting selected. This approach avoids the exponential growth of the number of modes during computation, thus generating a random sample of the complete set of EMs within reasonable time. We generated samples of different sizes for a metabolic network of Escherichia coli, and observed that they preserve several properties of the full EM set. It is also shown that EM sampling can be used for rational strain design. A well distributed sample, that is representative of the complete set of EMs, should be suitable to most EM-based methods for analysis and optimization of metabolic networks.
Source code for a cross-platform implementation in Python is freely available at http://code.google.com/p/emsampler.
dmachado@deb.uminho.pt
Supplementary data are available at Bioinformatics online.
Mass spectrometry imaging (MSI) simultaneously detects and identifies the spatial distribution of numerous molecules throughout tissues. Currently, MSI is limited to providing a static and ex vivo ...snapshot of highly dynamic systems in which molecules are constantly synthesized and consumed. Herein, we demonstrate an innovative MSI methodology to study dynamic molecular changes of amino acids within biological tissues by measuring the dilution and conversion of stable isotopes in a mouse model. We evaluate the method specifically on hepatocellular metabolism of the essential amino acid l‐phenylalanine, associated with liver diseases. Crucially, the method reveals the localized dynamics of l‐phenylalanine metabolism, including its in vivo hydroxylation to l‐tyrosine and co‐localization with other liver metabolites in a time course of samples from different animals. This method thus enables the dynamics of localized biochemical synthesis to be studied directly from biological tissues.
Imaging isotopes: A mass spectrometry imaging method using isotope labeling to study dynamic molecular changes of l‐phenylalanine (Phe) in mouse liver tissue was developed. Using this method, hydroxylation of Phe to l‐tyrosine (Tyr), as well as its co‐localization with other amino acids could be monitored. This study demonstrates the potential to spatially detect local molecular kinetics of amino acids in research and clinical applications.
Performance of controllers applied in biotechnological production is often below expectation. Online automatic tuning has the capability to improve control performance by adjusting control ...parameters. This work presents automatic tuning approaches for model reference specific growth rate control during fed-batch cultivation. The approaches are direct methods that use the error between observed specific growth rate and its set point; systematic perturbations of the cultivation are not necessary. Two automatic tuning methods proved to be efficient, in which the adaptation rate is based on a combination of the error, squared error and integral error. These methods are relatively simple and robust against disturbances, parameter uncertainties, and initialization errors. Application of the specific growth rate controller yields a stable system. The controller and automatic tuning methods are qualified by simulations and laboratory experiments with
Bordetella pertussis
.
Background Metabolic reprogramming is a common phenomenon in tumorigenesis and tumor progression. Amino acids are important mediators in cancer metabolism, and their kinetics in tumor tissue are far ...from being understood completely. Mass spectrometry imaging is capable to spatiotemporally trace important endogenous metabolites in biological tissue specimens. In this research, we studied L-ring-.sup.13C.sub.6-labeled phenylalanine and tyrosine kinetics in a human non-small cell lung carcinoma (NSCLC) xenografted mouse model using matrix-assisted laser desorption/ionization Fourier-transform ion cyclotron resonance mass spectrometry imaging (MALDI-FTICR-MSI). Methods We investigated the L-ring-.sup.13C.sub.6-Phenylalanine (.sup.13C.sub.6-Phe) and L-ring-.sup.13C.sub.6-Tyrosine (.sup.13C.sub.6-Tyr) kinetics at 10 min (n = 4), 30 min (n = 3), and 60 min (n = 4) after tracer injection and sham-treated group (n = 3) at 10 min in mouse-xenograft lung tumor tissues by MALDI-FTICR-MSI. Results The dynamic changes in the spatial distributions of 19 out of 20 standard amino acids are observed in the tumor tissue. The highest abundance of .sup.13C.sub.6-Phe was detected in tumor tissue at 10 min after tracer injection and decreased progressively over time. The overall enrichment of .sup.13C.sub.6-Tyr showed a delayed temporal trend compared to .sup.13C.sub.6-Phe in tumor caused by the Phe-to-Tyr conversion process. Specifically, .sup.13C.sub.6-Phe and .sup.13C.sub.6-Tyr showed higher abundances in viable tumor regions compared to non-viable regions. Conclusions We demonstrated the spatiotemporal intra-tumoral distribution of the essential aromatic amino acid .sup.13C.sub.6-Phe and its de-novo synthesized metabolite .sup.13C.sub.6-Tyr by MALDI-FTICR-MSI. Our results explore for the first time local phenylalanine metabolism in the context of cancer tissue morphology. This opens a new way to understand amino acid metabolism within the tumor and its microenvironment. Keywords: L-ring-.sup.13C.sub.6-Phenylalanine, L-ring-.sup.13C.sub.6-Tyrosine, Amino acids, Isotope labeling, Tumor, Mass spectrometry imaging
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► Controlled random search has preference over ranking for selecting active pathways. ► Generating vectors have preference over elementary modes. ► One to three pathways can represent ...a particular phenotype.
In metabolic systems, the cellular network of metabolic reactions together with constraints of (ir)reversibility of enzymes determines the space of all possible steady-state phenotypes. Analysis of large metabolic models, however, is not feasible in real-time and identification of a smaller model without loss of accuracy is desirable for model-based bioprocess optimization and control. To this end, we propose two search algorithms for systematic identification of a subset of pathways that match the observed cellular phenotype relevant for a particular process condition. Central carbon metabolism of
Escherichia coli was used as a case-study together with three phenotypic datasets obtained from the literature. The first search method is based on ranking pathways and the second is a controlled random search (CRS) algorithm. Since we wish to obtain a biologically realistic subset of pathways, the objective function to be minimized is a trade-off between the error and investment costs. We found that the CRS outperforms the ranking algorithm, as it is less likely to fall into local minima. In addition, we compared two pathway analysis methods (elementary modes versus generating vectors) in terms of modelling accuracy and computational intensity. We conclude that generating vectors have preference over elementary modes to describe a particular phenotype. Overall, the original model containing 433 generating vectors or 2706 elementary modes could be reduced to a system of one to three pathways giving a good correlation with the measured datasets. We consider this work as a first step towards the use of detailed metabolic models to improve real-time optimization, monitoring, and control of biological processes.
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