# characteristics.description[].text
Microbiome analyses of low-biomass samples are challenging because of contamination and inefficient amplification, leading many investigators to employ low-throughput methods with minimal controls. We developed a new automated protocol, KatharoSeq (from the Greek katharos, ???clean???), that outperforms single tube extractions while processing four times faster. KatharoSeq incorporates positive and negative controls to reveal the whole bacterial community from inputs of as little as 50 cells, and correctly identifies 90.6% (S.E. 0.013) of reads from 500 cells. To demonstrate the broad utility of KatharoSeq, we performed 16S rRNA amplicon (???16S??? below) and shotgun metagenome (???shotgun??? below) analyses of the Jet Propulsion Lab Spacecraft Assembly Facility, SAF, (n=192, 96), 52 rooms from a Neonatal Intensive Care Unit, NICU, (n=388, 384), and an endangered abalone rearing facility (n=192, 192), obtaining spatially resolved, unique microbiomes, reproducible across hundreds of samples. The SAF, our primary focus, contains thirty two sOTUs (sub-OTUs, defined as exact sequence matches and their inferred variants identified by the deblur algorithm with four (Acinetobacter lwoffi, Paracoccus marcusii, Mycobacterium sp., and Novosphingobium) being present in over 75 % of the samples. Using microbial spatial topography, the most abundant cleanroom contaminant, A. lwoffi, is related to human foot traffic exposure. In the NICU, we predict a patient disease outcome from the built environment, and in the abalone facility, we show that microbial communities reflect the marine environment rather than human input. Consequently, we demonstrate the feasibility and utility of large-scale, low biomass metagenomics analyses using the KatharoSeq protocol.