The advances in experimental methods and the development of high performance bioinformatic tools have substantially improved our understanding of microbial communities associated with human niches. Many studies have documented that changes in microbial abundance and composition of the human microbiome is associated with human health and diseased state. The majority of research on human microbiome is typically focused in the analysis of one level of biological information, i.e., metagenomics or metatranscriptomics. In this review, we describe some of the different experimental and bioinformatic strategies applied to analyze the 16S rRNA gene profiling and shotgun sequencing data of the human microbiome. We also discuss how some of the recent insights in the combination of metagenomics, metatranscriptomics and viromics can provide more detailed description on the interactions between microorganisms and viruses in oral and gut microbiomes. Recent studies on viromics have begun to gain importance due to the potential involvement of viruses in microbial dysbiosis. In addition, metatranscriptomic combined with metagenomic analysis have shown that a substantial fraction of microbial transcripts can be differentially regulated relative to their microbial genomic abundances. Thus, understanding the molecular interactions in the microbiome using the combination of metagenomics, metatranscriptomics and viromics is one of the main challenges towards a system level understanding of human microbiome.

Light chain-associated amyloidosis is a fatal disease characterized by the aggregation and pathologic deposition of monoclonal light chain-related fragments as amyloid fibrils in organs or tissues throughout the body. Notably, it has been observed that proteins encoded by the lambda variable light chain (V(L)) gene segment 6a are invariably associated with amyloid deposition; however, the contribution of the gene to this phenomenon has not been established. In this regard, we have determined the thermodynamic stability and kinetics of in vitro fibrillogenesis of a recombinant (r) V(L) protein, designated 6aJL2, which contains the predicted sequences encoded by the 6a and JL2 germline genes. Additionally, we studied a 6a mutant (6aJL2-Arg25Gly), that is present in approximately 25% of all amyloid-associated lambda6 light chains. Remarkably, the wild-type 6aJL2 protein was more stable than were all known amyloidogenic kappa and lambda light chains for which stability parameters are available; more importantly, it was even more so (and less fibrillogenic) than the only clinically proven nonamyloidogenic lambda6 protein, Jto. Conversely, the mutated 6aJL2-R25G molecule was considerably less stable and more fibrillogenic than was the native 6aJL2. Our data indicate that the propensity of lambda6 light chains to form amyloid can not be attributed to thermodynamic instability of the germline-encoded Vlambda6 domain, but rather, is dependent on sequence alterations that render such proteins amyloidogenic.

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