Modularization of biochemical networks based on classification of Petri net t-invariants

<p>Abstract</p> <p>Background</p> <p>Structural analysis of biochemical networks is a growing field in bioinformatics and systems biology. The availability of an increasing amount of biological data from molecular biological networks promises a deeper understanding but confronts researchers with the problem of combinatorial explosion. The amount of qualitative network data is growing much faster than the amount of quantitative data, such as enzyme kinetics. In many cases it is even impossible to measure quantitative data because of limitations of experimental methods, or for ethical reasons. Thus, a huge amount of qualitative data, such as interaction data, is available, but it was not sufficiently used for modeling purposes, until now. New approaches have been developed, but the complexity of data often limits the application of many of the methods. Biochemical Petri nets make it possible to explore static and dynamic qualitative system properties. One Petri net approach is model validation based on the computation of the system's invariant properties, focusing on t-invariants. T-invariants correspond to subnetworks, which describe the basic system behavior.</p> <p>With increasing system complexity, the basic behavior can only be expressed by a huge number of t-invariants. According to our validation criteria for biochemical Petri nets, the necessary verification of the biological meaning, by interpreting each subnetwork (t-invariant) manually, is not possible anymore. Thus, an automated, biologically meaningful classification would be helpful in analyzing t-invariants, and supporting the understanding of the basic behavior of the considered biological system.</p> <p>Methods</p> <p>Here, we introduce a new approach to automatically classify t-invariants to cope with network complexity. We apply clustering techniques such as UPGMA, Complete Linkage, Single Linkage, and Neighbor Joining in combination with different distance measures to get biologically meaningful clusters (t-clusters), which can be interpreted as modules. To find the optimal number of t-clusters to consider for interpretation, the cluster validity measure, Silhouette Width, is applied.</p> <p>Results</p> <p>We considered two different case studies as examples: a small signal transduction pathway (pheromone response pathway in <it>Saccharomyces cerevisiae</it>) and a medium-sized gene regulatory network (gene regulation of Duchenne muscular dystrophy). We automatically classified the t-invariants into functionally distinct t-clusters, which could be interpreted biologically as functional modules in the network. We found differences in the suitability of the various distance measures as well as the clustering methods. In terms of a biologically meaningful classification of t-invariants, the best results are obtained using the Tanimoto distance measure. Considering clustering methods, the obtained results suggest that UPGMA and Complete Linkage are suitable for clustering t-invariants with respect to the biological interpretability.</p> <p>Conclusion</p> <p>We propose a new approach for the biological classification of Petri net t-invariants based on cluster analysis. Due to the biologically meaningful data reduction and structuring of network processes, large sets of t-invariants can be evaluated, allowing for model validation of qualitative biochemical Petri nets. This approach can also be applied to elementary mode analysis.</p

Genetic and Structural Diversity of Prokaryotic Ice-Binding Proteins from the Central Arctic Ocean

Ice-binding proteins (IBPs) are a group of ecologically and biotechnologically relevant enzymes produced by psychrophilic organisms. Although putative IBPs containing the domain of unknown function (DUF) 3494 have been identified in many taxa of polar microbes, our knowledge of their genetic and structural diversity in natural microbial communities is limited. Here, we used samples from sea ice and sea water collected in the central Arctic Ocean as part of the MOSAiC expedition for metagenome sequencing and the subsequent analyses of metagenome-assembled genomes (MAGs). By linking structurally diverse IBPs to particular environments and potential functions, we reveal that IBP sequences are enriched in interior ice, have diverse genomic contexts and cluster taxonomically. Their diverse protein structures may be a consequence of domain shuffling, leading to variable combinations of protein domains in IBPs and probably reflecting the functional versatility required to thrive in the extreme and variable environment of the central Arctic Ocean

Genetic and Structural Diversity of Prokaryotic Ice-Binding Proteins from the Central Arctic Ocean

Ice-binding proteins (IBPs) are a group of ecologically and biotechnologically relevant enzymes produced by psychrophilic organisms. Although putative IBPs containing the domain of unknown function (DUF) 3494 have been identified in many taxa of polar microbes, our knowledge of their genetic and structural diversity in natural microbial communities is limited. Here, we used samples from sea ice and sea water collected in the central Arctic Ocean as part of the MOSAiC expedition for metagenome sequencing and the subsequent analyses of metagenome-assembled genomes (MAGs). By linking structurally diverse IBPs to particular environments and potential functions, we reveal that IBP sequences are enriched in interior ice, have diverse genomic contexts and cluster taxonomically. Their diverse protein structures may be a consequence of domain shuffling, leading to variable combinations of protein domains in IBPs and probably reflecting the functional versatility required to thrive in the extreme and variable environment of the central Arctic Ocean

Risk Factors for Preterm Birth following Open Fetal Myelomeningocele Repair: Results from a Prospective Cohort

BACKGROUND Fetal myelomeningocele (fMMC) repair is a therapeutic option in selected cases. This study aimed to identify risk factors for preterm birth (PTB) following open fMMC repair. METHODS Sixty-seven women underwent fMMC repair and delivered a baby between 2010 and 2018 at our center. Demographic, surgical, and pregnancy complications, including potential risk factors for PTB such as preterm premature rupture of membranes (PPROM), chorioamniotic membrane separation (CMS), and placental abruption were evaluated. RESULTS Maternal body mass index, maternal age, parity, previous uterine surgery, gestational age at fetal surgery, total surgery duration, surgical subcutaneous hematoma, oligohydramnios, and amniotic fluid leakage were not identified as risk factors for PTB. CMS (p = 0.028, 92 vs. 52%) and PPROM (p = 0.001, 95 vs. 52%) were highly associated with PTB. Placental abruption was found more often in women after fMMC repair than in a general obstetrical population (12 vs. 1%) and ended in premature birth in all cases (p = 0.024, 100 vs. 60%). However, the majority of women delivered at a gestational age >35 weeks. CONCLUSIONS In our study cohort, risk factors for PTB were PPROM, CMS, and placental abruption, whereas surgery duration did not influence outcome. We conclude that the surgery technique should aim to minimize CMS and amniotic fluid leakage

An example of a Petri net with its incidence matrix, the corresponding linear equation system for the computation of t-invariants, and the resulting solution vectors

<p><b>Copyright information:</b></p><p>Taken from "Modularization of biochemical networks based on classification of Petri net t-invariants"</p><p>http://www.biomedcentral.com/1471-2105/9/90</p><p>BMC Bioinformatics 2008;9():90-90.</p><p>Published online 8 Feb 2008</p><p>PMCID:PMC2277402.</p><p></p

Real-world experience with capmatinib in MET exon 14-mutated non-small cell lung cancer (RECAP): a retrospective analysis from an early access program

Background: Patients with non-small cell lung cancer (NSCLC) presenting with mesenchymal–epithelial transition (MET) exon 14 skipping mutation have an unfavorable prognosis with standard treatments. Capmatinib is a selective MET inhibitor, which showed promising efficacy in this patient population in early trials. Methods: We performed a retrospective, international, multicenter efficacy and safety analysis in patients with NSCLC treated with capmatinib in an early access program between March 2019 and December 2021. Results: Data from 81 patients with advanced MET exon 14 mutated NSCLC treated with capmatinib in first- or later-line therapy were analyzed. Median age was 77 years (range, 48–91), 56% were women, 86% had stage IV disease, and 27% had brain metastases. For all patients, the objective response rate (ORR) to capmatinib was 58% (95% CI, 47–69), whereas it was 68% (95% CI, 50–82) in treatment-naïve and 50% (95% CI, 35–65) in pretreated patients. The median progression-free survival was 9.5 months (95% CI, 4.7–14.3), whereas it was 10.6 months (95% CI, 5.5–15.7) in first-line and 9.1 months (95% CI, 3.1–15.1) in pretreated patients. After a median follow-up of 11.0 months, the median overall survival was 18.2 months (95% CI, 13.2–23.1). In patients with measurable brain metastases (n = 11), the intracranial ORR was 46% (95% CI, 17–77). Capmatinib showed a manageable safety profile. Grade ⩾ 3 treatment-related adverse events included peripheral edema (13%), elevated creatinine (4%), and elevated liver enzymes (3%). Conclusion: In patients with MET exon 14 skipping mutation, capmatinib showed durable systemic and intracranial efficacy and a manageable safety profile. This analysis confirms previously reported phase II data in a real-world setting

Real-world experience with capmatinib in MET exon 14-mutated non-small cell lung cancer (RECAP) : a retrospective analysis from an early access program

Background: Patients with non-small cell lung cancer (NSCLC) presenting with mesenchymal-epithelial transition (MET) exon 14 skipping mutation have an unfavorable prognosis with standard treatments. Capmatinib is a selective MET inhibitor, which showed promising efficacy in this patient population in early trials. Methods: We performed a retrospective, international, multicenter efficacy and safety analysis in patients with NSCLC treated with capmatinib in an early access program between March 2019 and December 2021. Results: Data from 81 patients with advanced MET exon 14 mutated NSCLC treated with capmatinib in first- or later-line therapy were analyzed. Median age was 77 years (range, 48-91), 56% were women, 86% had stage IV disease, and 27% had brain metastases. For all patients, the objective response rate (ORR) to capmatinib was 58% (95% CI, 47-69), whereas it was 68% (95% CI, 50-82) in treatment-naive and 50% (95% CI, 35-65) in pretreated patients. The median progression-free survival was 9.5 months (95% CI, 4.7-14.3), whereas it was 10.6 months (95% CI, 5.5-15.7) in first-line and 9.1 months (95% CI, 3.1-15.1) in pretreated patients. After a median follow-up of 11.0 months, the median overall survival was 18.2 months (95% CI, 13.2-23.1). In patients with measurable brain metastases (n = 11), the intracranial ORR was 46% (95% CI, 17-77). Capmatinib showed a manageable safety profile. Grade &amp;gt; 3 treatment-related adverse events included peripheral edema (13%), elevated creatinine (4%), and elevated liver enzymes (3%). Conclusion: In patients with MET exon 14 skipping mutation, capmatinib showed durable systemic and intracranial efficacy and a manageable safety profile. This analysis confirms previously reported phase II data in a real-world setting.Funding Agencies|Karl Landsteiner Institute for Lung Research and Pulmonary Oncology</p