LooplessFluxSampler: an efficient toolbox for sampling the loopless flux solution space of metabolic models.

BACKGROUND: Uniform random sampling of mass-balanced flux solutions offers an unbiased appraisal of the capabilities of metabolic networks. Unfortunately, it is impossible to avoid thermodynamically infeasible loops in flux samples when using convex samplers on large metabolic models. Current strategies for randomly sampling the non-convex loopless flux space display limited efficiency and lack theoretical guarantees. RESULTS: Here, we present LooplessFluxSampler, an efficient algorithm for exploring the loopless mass-balanced flux solution space of metabolic models, based on an Adaptive Directions Sampling on a Box (ADSB) algorithm. ADSB is rooted in the general Adaptive Direction Sampling (ADS) framework, specifically the Parallel ADS, for which theoretical convergence and irreducibility results are available for sampling from arbitrary distributions. By sampling directions that adapt to the target distribution, ADSB traverses more efficiently the sample space achieving faster mixing than other methods. Importantly, the presented algorithm is guaranteed to target the uniform distribution over convex regions, and it provably converges on the latter distribution over more general (non-convex) regions provided the sample can have full support. CONCLUSIONS: LooplessFluxSampler enables scalable statistical inference of the loopless mass-balanced solution space of large metabolic models. Grounded in a theoretically sound framework, this toolbox provides not only efficient but also reliable results for exploring the properties of the almost surely non-convex loopless flux space. Finally, LooplessFluxSampler includes a Markov Chain diagnostics suite for assessing the quality of the final sample and the performance of the algorithm.

Method for lineage typing of epidemic Renibacterium salmoninarum in Chilean salmon farms.

Renibacterium salmoninarum (Rs) is the etiological agent of bacterial kidney disease (BKD), which significantly affects farmed and wild salmonids worldwide. Although the whole genome of Rs (~3.1 million nucleotides) is highly conserved, genomic epidemiology analyses have identified four sub-lineages from Chilean isolates. A total of 94 Rs genomes from the BIGSdb aquaculture database were aligned and compared using bioinformatics tools, identifying 2199 independent single-nucleotide polymorphisms (SNPs) spread along the genome. A detailed analysis of the distribution of the SNPs showed five local zones of a length in the range of 10-15 kbp that should be used to unambiguously identify a specific sub-lineage. Based on the Rs type strain DSM 20767T , we designed multiplex PCR primers that produce specific amplification products which were further sequenced by the Sanger method to obtain the genotype of the sub-lineage. For the genetic typing, we evaluated 27 Rs isolates recovered from BKD outbreaks from different fish species and regions of Chile. Based on the findings reported here, we propose the PCR approach as a valuable tool for the rapid and reliable studying of the relationships between Rs isolates and the different sub-lineages without requiring the sequencing of the entire genome.