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The annotation of small molecules is one of the most challenging and important steps in untargeted mass spectrometry analysis, as most of our biological interpretations rely on structural annotations. Molecular networking has emerged as a structured way to organize and mine data from untargeted tandem mass spectrometry (MS/MS) experiments and has been widely applied to propagate annotations. However, propagation is done through manual inspection of MS/MS spectra connected in the spectral networks and is only possible when a reference library spectrum is available. One of the alternative approaches used to annotate an unknown fragmentation mass spectrum is through the use of in silico predictions. One of the challenges of in silico annotation is the uncertainty around the correct structure among the predicted candidate lists. Here we show how molecular networking can be used to improve the accuracy of in silico predictions through propagation of structural annotations, even when there is no match to a MS/MS spectrum in spectral libraries. This is accomplished through creating a network consensus of re-ranked structural candidates using the molecular network topology and structural similarity to improve in silico annotations. The Network Annotation Propagation (NAP) tool is accessible through the GNPS web-platform https://gnps.ucsd.edu/ProteoSAFe/static/gnps-theoretical.jsp.

Antimicrobial resistance is a global health crisis and few novel antimicrobials have been discovered in recent decades. Natural products, particularly from Streptomyces, are the source of most antimicrobials, yet discovery campaigns focusing on Streptomyces from the soil largely rediscover known compounds. Investigation of understudied and symbiotic sources has seen some success, yet no studies have systematically explored microbiomes for antimicrobials. Here we assess the distinct evolutionary lineages of Streptomyces from insect microbiomes as a source of new antimicrobials through large-scale isolations, bioactivity assays, genomics, metabolomics, and in vivo infection models. Insect-associated Streptomyces inhibit antimicrobial-resistant pathogens more than soil Streptomyces. Genomics and metabolomics reveal their diverse biosynthetic capabilities. Further, we describe cyphomycin, a new molecule active against multidrug resistant fungal pathogens. The evolutionary trajectories of Streptomyces from the insect microbiome influence their biosynthetic potential and ability to inhibit resistant pathogens, supporting the promise of this source in augmenting future antimicrobial discovery.

Given the complexity of host-microbiota symbioses, scientists and philosophers are asking questions at new biological levels of hierarchical organization—what is a holobiont and hologenome? When should this vocabulary be applied? Are these concepts a null hypothesis for host-microbe systems or limited to a certain spectrum of symbiotic interactions such as host-microbial coevolution? Critical discourse is necessary in this nascent area, but productive discourse requires that skeptics and proponents use the same lexicon.

Oil in subsurface reservoirs is biodegraded by resident microbial communities. Water-mediated, anaerobic conversion of hydrocarbons to methane and CO2, catalyzed by syntrophic bacteria and methanogenic archaea, is thought to be one of the dominant processes. We compared 160 microbial community compositions in ten hydrocarbon resource environments (HREs) and sequenced twelve metagenomes to characterize their metabolic potential. Although anaerobic communities were common, cores from oil sands and coal beds had unexpectedly high proportions of aerobic hydrocarbon-degrading bacteria. Likewise, most metagenomes had high proportions of genes for enzymes involved in aerobic hydrocarbon metabolism. Hence, although HREs may have been strictly anaerobic and typically methanogenic for much of their history, this may not hold today for coal beds and for the Alberta oil sands, one of the largest remaining oil reservoirs in the world. This finding may influence strategies to recover energy or chemicals from these HREs by in situ microbial processes.

Natural products profoundly impact many research areas, including medicine, organic chemistry, and cell biology. However, discovery of new natural products suffers from a lack of high throughput analytical techniques capable of identifying structural novelty in the face of a high degree of chemical redundancy. Methods to select bacterial strains for drug discovery have historically been based on phenotypic qualities or genetic differences and have not been based on laboratory production of secondary metabolites. Therefore, untargeted LC/MS-based secondary metabolomics was evaluated to rapidly and efficiently analyze marine-derived bacterial natural products using LC/MS-principal component analysis (PCA). A major goal of this work was to demonstrate that LC/MS-PCA was effective for strain prioritization in a drug discovery program. As proof of concept, we evaluated LC/MS-PCA for strain selection to support drug discovery, for the discovery of unique natural products, and for rapid assessment of regulation of natural product production.

Bioassay-guided metabolomic analyses led to the characterization of four new 20-membered glycosylated polyketide macrolactams – macrotermycins A-D – from a termite-associated actinomycete, Amycolatopsis sp. M39. M39’s sequenced genome revealed the macrotermycin’s putative biosynthetic gene cluster. Macrotermycins A and C had antibacterial activity against human-pathogenic S. aureus and of greater ecological relevance, they also had selective antifungal activity against a fungal parasite of the termite fungal garden.

Starch-hydrolyzing enzymes lacking ␣-glucan-specific carbohydrate-binding modules (CBMs) typically have lowered activity on granular starch relative to their counterparts with CBMs. Thus, consideration of starch recognition by CBMs is a key factor in understanding granular starch hydrolysis. To this end, we have dissected the modular structure of the maltohexaose-forming amylase from Bacillus halodurans (C-125). This five-module protein comprises an N-terminal family 13 catalytic module followed in order by two modules of unknown function, a family 26 CBM (BhCBM26), and a family 25 CBM (BhCBM25). Here we present a comprehensive structure-function analysis of starch and ␣-glucooligosaccharide recognition by BhCBM25 and BhCBM26 using UV methods, isothermal titration calorimetry, and x-ray crystallography. The results reveal that the two CBMs bind ␣-glucooligosaccharides, particularly those containing ␣-1,6 linkages, with different affinities but have similar abilities to bind granular starch. Notably, these CBMs appear to recognize the same binding sites in granular starch. The enhanced affinity of the tandem CBMs for granular starch is suggested to be the main biological advantage for this enzyme to contain two CBMs. Structural studies of the native and ligandbound forms of BhCBM25 and BhCBM26 show a structurally conserved mode of ligand recognition but through non-sequence-conserved residues. Comparison of these CBM structures with other starch-specific CBM structures reveals a generally conserved mode of starch recognition.It is well established that carbohydrates play vital roles in numerous biological settings. They can act as the carriers of biological information, such as in cell development, carcinogenesis, immune response, and cell trafficking; as structural macromolecules, such as the cellulose of plant cell walls or chitin of insect exoskeletons; or as an energy source. Polysaccharides, which are a highly polymerized class of carbohydrates, can perform any of these functions. As mentioned, cellulose and chitin, the first and second most abundant biopolymers on earth, respectively, are the premier structural carbohydrates. Glycosaminoglycans are a highly complex class of polysaccharides that make up the extracellular glue of mammalian tissues and function both in structural and information content roles. Glycogen and starch are related polysaccharides that function as the primary storage carbohydrates in animals and plants, respectively.Glycogen is a polymer of glucose comprising linear ␣-1,4-linked glucose with ␣-1,6 branch points occurring approximately every 8 -12 glucose residues. Amylopectin, a component of starch, is a glycogen-like molecule but with ␣-1,6 branch points occurring approximately every 24 -30 glucose residues. Amylose, the other component of starch, is a polymer of pure linear ␣-1,4-linked glucose. The ␣-1,4 linkages in these polysaccharides make them fold into tight helical structures, resulting in dense granules that function as highly effective storage systems. The release of small...