Deconvolving molecular signatures of interactions between microbial colonies.

MOTIVATION: The interactions between microbial colonies through chemical signaling are not well understood. A microbial colony can use different molecules to inhibit or accelerate the growth of other colonies. A better understanding of the molecules involved in these interactions could lead to advancements in health and medicine. Imaging mass spectrometry (IMS) applied to co-cultured microbial communities aims to capture the spatial characteristics of the colonies' molecular fingerprints. These data are high-dimensional and require computational analysis methods to interpret. RESULTS: Here, we present a dictionary learning method that deconvolves spectra of different molecules from IMS data. We call this method MOLecular Dictionary Learning ( MOLDL: ). Unlike standard dictionary learning methods which assume Gaussian-distributed data, our method uses the Poisson distribution to capture the count nature of the mass spectrometry data. Also, our method incorporates universally applicable information on common ion types of molecules in MALDI mass spectrometry. This greatly reduces model parameterization and increases deconvolution accuracy by eliminating spurious solutions. Moreover, our method leverages the spatial nature of IMS data by assuming that nearby locations share similar abundances, thus avoiding overfitting to noise. Tests on simulated datasets show that this method has good performance in recovering molecule dictionaries. We also tested our method on real data measured on a microbial community composed of two species. We confirmed through follow-up validation experiments that our method recovered true and complete signatures of molecules. These results indicate that our method can discover molecules in IMS data reliably, and hence can help advance the study of interaction of microbial colonies. AVAILABILITY AND IMPLEMENTATION: The code used in this paper is available at: https://github.com/frizfealer/IMS_project.

Genetic and morphological variability of the European mudminnow Umbra krameri (Teleostei, Umbridae) in Serbia and in Bosnia and Herzegovina, a basis for future conservation activities.

As a basis for future conservation activities, the genetic and external body morphology variability of the European mudminnow Umbra krameri, a highly endangered fish species in Serbia and in Bosnia and Herzegovina, was determined for existing populations with the use of molecular markers (mitochondrial and microsatellite DNA) and geometric morphometric methods. Mitochondrial DNA cytochrome b gene analysis revealed two previously undescribed haplotypes: Da1 (the Lugomir population from the Danube River basin) and Sa1 (the Bakreni Batar and the Gromizelj populations from the Sava River system), with a corresponding genetic distance of 0·7%. Paired values of FST and DAS distances for microsatellite marker data show that the difference between the Danube and the Sava populations is seven to nine times higher than the difference between the populations within the Sava River system. Geometric morphometric analyses also support a clear separation of the Lugomir population from the Bakreni Batar and the Gromizelj populations. The analysis of the body shape variation, however, indicates a significant difference between the two genetically indistinguishable Sava populations. The observed genetic and phenetic relationships of the analysed mudminnow populations most probably represent a consequence of historical, geographical and ecological factors. These results will offer guidelines for future protection, conservation and sustainable management of this species in the region.

AMP: Assembly Matching Pursuit.

Metagenomics, the study of the total genetic material isolated from a biological host, promises to reveal host-microbe or microbe-microbe interactions that may help to personalize medicine or improve agronomic practice. We introduce a method that discovers metagenomic units (MGUs) relevant for phenotype prediction through sequence-based dictionary learning. The method aggregates patient-specific dictionaries and estimates MGU abundances in order to summarize a whole population and yield universally predictive biomarkers. We analyze the impact of Gaussian, Poisson, and Negative Binomial read count models in guiding dictionary construction by examining classification efficiency on a number of synthetic datasets and a real dataset from Ref. 1. Each outperforms standard methods of dictionary composition, such as random projection and orthogonal matching pursuit. Additionally, the predictive MGUs they recover are biologically relevant.

Two-module organization of the mandible in the yellow-necked mouse: a comparison between two different morphometric approaches.

Mandibles of yellow-necked mouse (Apodemus flavicollis) were used to explore modularity. We tested a biological hypothesis that two separate modules (alveolar region and ascending ramus) can be recognized within the mandible. As a second research goal, we compared two different morphometric procedures under the assumption that methodological approaches that use either geometric or traditional morphometric techniques should give similar results. Besides confirmation of the predicted hypothesis of modularity, the application of both approaches revealed that: (i) modularity was somewhat more evident when it was analysed on the asymmetric (fluctuating asymmetry, FA) than on the symmetric (individual variation) component of variation; (ii) there is correspondence in the patterns of individual variation and FA, which indicates that integration of mandibular traits among individuals is primarily due to direct developmental interactions; and (iii) allometry does not obscure the hypothesized modularity for individual variation or for FA. In addition, traditional morphometric method allowed us to check whether allometry influenced each module to the same extent and to conclude that the ascending ramus is more heavily influenced by general size than the alveolar region. In studies of modularity, differences in methods can lead to discrepancies in the results, and therefore, some caution is required when comparing findings from different investigations. The substantial agreement between our results provides evidence that, when considering two-module organization of the mouse mandible, direct comparison among studies that use the methods applied herein is, in great part, reliable.