There is increasing interest in employing shotgun sequencing, rather than amplicon sequencing, to analyze microbiome samples. Typical projects may involve hundreds of samples and billions of sequencing reads. The comparison of such samples against a protein reference database generates billions of alignments and the analysis of such data is computationally challenging. To address this, we have substantially rewritten and extended our widely-used microbiome analysis tool MEGAN so as to facilitate the interactive analysis of the taxonomic and functional content of very large microbiome datasets. Other new features include a functional classifier called InterPro2GO, gene-centric read assembly, principal coordinate analysis of taxonomy and function, and support for metadata. The new program is called MEGAN Community Edition (CE) and is open source. By integrating MEGAN CE with our high-throughput DNA-to-protein alignment tool DIAMOND and by providing a new program MeganServer that allows access to metagenome analysis files hosted on a server, we provide a straightforward, yet powerful and complete pipeline for the analysis of metagenome shotgun sequences. We illustrate how to perform a full-scale computational analysis of a metagenomic sequencing project, involving 12 samples and 800 million reads, in less than three days on a single server. All source code is available here: https://github.com/danielhuson/megan-ce

Highlights d High AMY1 copy number (CN) is associated with higher levels of Porphyromonas in saliva d High AMY1-CN stool has more resistant starch degraders; drives more adiposity in GF mice d Stool short-chain fatty acid levels are predictive of salivary amylase activity d Upon diet standardization, gut microbiomes converged without eliminating differences

The human gut forms a dynamic reservoir of antibiotic resistance genes (ARGs). Treatment with antimicrobial agents has a significant impact on the intestinal resistome and leads to enhanced horizontal transfer and selection of resistance. We have monitored the development of intestinal ARGs over a 6-day course of ciprofloxacin (Cp) treatment in two healthy individuals by using sequenced-based metagenomics and different ARG quantification methods. Fixed-and random-effect models were applied to determine the change in ARG abundance per defined daily dose of Cp as an expression of the respective selection pressure. Among various shifts in the composition of the intestinal resistome, we found in one individual a strong positive selection for class D beta-lactamases which were partly located on a mobile genetic element. Furthermore, a trend to a negative selection has been observed with class A beta-lactamases (؊2.66 hits per million sample reads/defined daily dose; P ‫؍‬ 0.06). By 4 weeks after the end of treatment, the composition of ARGs returned toward their initial state but to a different degree in both subjects. We present here a novel analysis algorithm for the determination of antibiotic selection pressure which can be applied in clinical settings to compare therapeutic regimens regarding their effect on the intestinal resistome. This information is of critical importance for clinicians to choose antimicrobial agents with a low selective force on their patients' intestinal ARGs, likely resulting in a diminished spread of resistance and a reduced burden of hospital-acquired infections with multidrug-resistant pathogens.

Investment in SARS-CoV-2 sequencing in Africa over the past year has led to a major increase in the number of sequences generated, now exceeding 100,000 genomes, used to track the pandemic on the continent. Our results show an increase in the number of African countries able to sequence domestically, and highlight that local sequencing enables faster turnaround time and more regular routine surveillance. Despite limitations of low testing proportions, findings from this genomic surveillance study underscore the heterogeneous nature of the pandemic and shed light on the distinct dispersal dynamics of Variants of Concern, particularly Alpha, Beta, Delta, and Omicron, on the continent. Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve, while the continent faces many emerging and re-emerging infectious disease threats. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century.

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