Microbial Sequencing & Analytics Core

The Microbial Sequencing & Analytics Resource (MSAAR) is equipped with an epMotion® 7575tc liquid handling framework, assuring dependable and reproducible assay results. These instruments are purposed solely for microbiome nucleic extraction and library preparation of microbiome samples.

The MSAAR facility amplifies & prepares Illumina libraries for the following applications:

• 16S rRNA gene amplicons – we have oligos available for the V4 region of the gene
• Amplification of other variable regions of the 16S rRNA gene can be performed as needed
• ITS (Internal Transcribed Spacer DNA) & 18S rRNA gene amplicons
• Whole genome sequences of microbial species i.e. shotgun metagenomics
• RNA-Seq of microbial communities

All samples in the MSAAR facility undergo quality control (QC) procedures, ensuring the quantity and the quality of the nucleic acids and prepared libraries are fit to move forward in preparation for NGS (Next Generation Sequencing). Our QC services are also available to any investigator within the Cleveland Clinic and its affiliates.

The Microbial Sequencing & Analytics Resource (MSAAR) is equipped with illumina’s iSeq™ 100 Sequencing System for affordable, fast and efficient low-throughput sequencing. This instrument has a maximum output of 4 million reads, accommodating investigators who would like to:

• Run a small projects with a low number of samples
• Perform pilot studies
• Use as a QC run prior to MiSeq runs
• Generate grant submission data

• Amplicon Sequencing Analysis (16S rRNA, 18S rRNA, ITS)
• OTU clustering based e.g. Qiime and Mothur
• Sequence variant (SV) based e.g. DADA2 and Deblur
• 16s RNA amplicon sequencing based functional analysis (PiCRUSt and FAPROTAX)
• Shotgun sequencing based metagenomics, metatranscriptomics and RNA-Seq analysis
• Quality control and filtering (e.g. Quality based trimming, adapter/primer sequence removal, host sequence removal)
• Individual read based taxonomic and functional characterization (e.g. HUMAN2, Kraken and Metaphlan2)
• Individual read based antibiotic resistance gene analysis
• Sequence variant analysis
• De-novo genome, metagenome, metatranscriptomics assembly (e.g. SPADES, MetaSPADES, IDBA, Meta-IDBA)
• Assembly validation, gene calling and annotations (KEGG, CAZY, COGG etc.)
• De-novo genome reconstruction from metagenome assembly (i.e. contigs)
• Strain level characterization and comparative genomics of the reconstructed genomes
• Antibiotics resistance gene analysis using assembly (i.e. contigs)

• Power Calculations (sample size estimation)
• Differential feature selection analysis
• Confounding factor identification and correction
• Biomarker identification
• Association analysis (e.g. MGWAS, WGCNA and GLM’s)
• Machine learning based model creation and validation (prediction and classification)
• Publication quality plot generation and sequence data submission (e.g. EMBL and NCBI)

• Microbial species/strain selection for Metabolic modeling
• Constraint based metabolic model creation of microbial genomes
• Constraint based metabolic model creation from host specific RNA-Seq or microbiome data
• Creation of host-microbiome metabolic model from microbial and host-specific metabolic models
• Simulation and flux balance analysis on microbial community model and/or host-microbiome metabolic model
• Identification of metabolites that can help increase and/or decrease the abundance of microbial and host cells
• Designing in-vivo and/or in-vitro experiments to validate metabolic modelling results