About — ABYSS

🌊 What is ABYSS?

ABYSS (Acinetobacter baumannii Yielding Surveillance System) is a comprehensive genomic resource that integrates typing, resistance, virulence, and epidemiological metadata for publicly available Acinetobacter baumannii genomes into a single, queryable, user-friendly interface.

A. baumannii is the WHO's priority-1 critical pathogen for new antibiotic development, the archetypal cause of ventilator-associated pneumonia, and one of the few organisms on Earth that can survive for weeks on a dry hospital surface. Existing resources present fragments of the surveillance picture — a typing database here, a resistance catalogue there, an ICU outbreak report somewhere else. ABYSS brings them together.

59KGenomes Indexed

96%Country Coverage

95%Year Coverage

83%Source Coverage

🔬ICU-focused lens

100%Open Access

🌊 The name

abyss (n.) — an immeasurably deep gulf or great space.

Acinetobacter baumannii lives in the abyss. Not the deep ocean — the deep hospital. The ventilator tubing. The mattress rail. The dry surface at 3am that nobody swabbed. The gap between equipment that infection control has stopped looking at.

These are the overlooked reservoirs of the ICU — the small, dark spaces where carbapenem-resistant A. baumannii survives for weeks, colonises the next patient, and waits. Surveillance fails in exactly those places, because we tend to look where we've always looked.

ABYSS descends into those spaces. From the genomes already sequenced and already public, the resource yields the surveillance that routine ICU rounds miss — every respiratory isolate, every bloodstream infection, every catheter tip, every dry-surface swab. It is a watch kept over the parts of the hospital nobody thinks to watch.

— Named in the ARGUS tradition: a watchful figure, a hundred eyes, a night that never sleeps.

🎯 Why ABYSS?

Acinetobacter baumannii is one of the three or four organisms that most directly determine whether an ICU can safely treat its sickest patients. It is:

The WHO priority-1 critical pathogen for new antibiotic development
A leading cause of ventilator-associated pneumonia and ICU bloodstream infections
Capable of surviving weeks on dry surfaces — the reason ICU outbreaks close wards
An organism for which pan-drug-resistant strains already exist

Global genomic surveillance is essential for tracking emergent clones, understanding carbapenem-resistance mechanisms, and informing infection control. The data exists. What hasn't existed is a way to actually use it without weeks of setup.

🔒 The retrieval bottleneck

A typical surveillance question — "give me all IC2 isolates from respiratory sources in West Africa that carry OXA-23" — requires, in the current ecosystem, that you either:

Download and re-annotate the entire repository locally (weeks of compute)
Write custom scripts to query static TSV archives (breaks with every update)
Manually navigate multiple standalone tools (hours per query, doesn't scale)

None of these works for a researcher in a low-resource setting with a laptop. None works for a clinical microbiologist who needs an answer this afternoon. And none produces the one thing every downstream tool actually consumes: a clean accession list.

🌊 What ABYSS changes

ABYSS places accession retrieval at the centre of the interface. Filter by genotype, geography, or resistance mechanism — combine any criteria — and download a plain-text list ready for datasets download genome accession --inputfile list.txt.

⚡

Filter → export in seconds

Combine MLST, IC lineage, K-locus, AMR mechanism, country, source, host, and collection year. Get the accession list instantly.

🔗

Typing and resistance together

MLST (Oxford), K-locus capsule, AMR, virulence, plasmid replicons — integrated into one master view.

🏥

ICU lens built in

Source categories collapse into epidemiological super-groups, with a headline ICU-association KPI on the geography page.

💊

Carbapenemase-aware

OXA-23, OXA-24/40, OXA-58, OXA-143, OXA-235, NDM, VIM, KPC — tracked individually, filterable in the AMR module.

📊

Interactive statistics

A live dashboard with filterable donuts, rankings, timelines, and a crosstab explorer.

🌐

Zero barrier to entry

No login. No API key. No cost. Runs in your browser over HTTPS. Works on a phone.

Why it matters: Genomic surveillance belongs to everyone, not just to hospitals with bioinformaticians on staff. ABYSS exists to close that gap — one accession list at a time.

👁️

ARGUS

Antimicrobial Resistance Genomic Unified Surveillance

ABYSS is the third resource in ARGUS — a family of independent, open genomic surveillance sites, each dedicated to one of the WHO priority ESKAPE pathogens. Every resource shares the same architecture: accession-first, metadata-integrated, no login, no install, MIT-licensed. Each has its own name, its own DOI, and its own community.

Named for Argus Panoptes — the hundred-eyed giant of Greek myth who never slept — the umbrella is a bet that AMR surveillance has to be unified to be useful, and that the pathogens driving the crisis deserve the same treatment.

🏆KLEOS

K. pneumoniae

PLANNED

💧PSEUDA

P. aeruginosa

PLANNED

👑EMPIRE

E. faecium

PLANNED

🌀ENTROPY

Enterobacter

PLANNED

Status as of 2026-10-13. SAURUS, ECLIPSE, and ABYSS are all live. ABYSS is the first resource to use an epidemiological super-group model tuned to the ICU. The remaining pathogens are on the roadmap and will ship as their pipelines are built and validated.

🗺️ Roadmap

ABYSS is built incrementally toward a single milestone: complete typing annotation of every public A. baumannii genome in the NCBI Assembly database.

v0.1 — Metadata foundation LIVE
59,160 accessions indexed with country, source, host, and year from NCBI BioSample. GCA↔GCF deduplication via numeric stem. Geography page live.
v0.2 — Full typing layer LIVE
48,038 genomes typed through AcinetoScope and the Shelenkov 2024 dataset — Pasteur + Oxford MLST, IC1–IC12 assignment, Kaptive K-locus capsule, AMRFinderPlus (carbapenemase-aware), VFDB, PlasmidFinder. All 12 pages live: MLST, Capsule, Master, AMR, Virulence, Plasmid, Statistics, Geography, Lineages, Downloads.
v0.3 — Full public collection IN PROGRESS
Extend typing to the remaining NCBI Assembly collection — both GCF (RefSeq) and GCA (GenBank) genomes — to reach the full ~59,000 accession base indexed in v0.1.
v1.0 — Full resource
All public genomes typed · citable Zenodo DOI · frozen, versioned release · peer-reviewed methods manuscript.

📦 Data sources

ABYSS combines three publicly available resources into a single integrated view:

1. Genome assemblies — NCBI Assembly

Every genome in ABYSS is sourced from the NCBI Assembly database. Accessions are the primary key. Where both a GenBank (GCA_) and RefSeq (GCF_) version exist, the RefSeq version is preferred; assemblies with no RefSeq counterpart are kept as GenBank.

2. Epidemiological metadata — NCBI BioSample

Country of origin, isolation source, host species, and collection year were extracted from NCBI BioSample records attached to each assembly. Source values were normalised into broad clinical, environmental, food, and animal categories while preserving the raw submitter strings for provenance. Coverage: 96% country, 83% source, 91% host, 95% year.

3. Typing annotations — generated by AcinetoScope

MLST (Oxford and Pasteur schemes) and K-locus capsule annotations are produced with AcinetoScope, the species-optimized typing pipeline published in Scientific Reports (2026).

4. Gene presence/absence — Shelenkov et al. (2024)

Antimicrobial resistance genes, virulence factors (VFDB), and plasmid replicons were sourced from the A. baumannii genomic epidemiology dataset published by Shelenkov, Mikhaylova & Akimkin in Data (MDPI), 2024. The original wide matrices were re-processed into long-format TSVs (accession × gene) to enable interactive retrieval in ABYSS.

⚙️ Methods & tools

All typing annotations in ABYSS are produced by AcinetoScope — an automated, comprehensive pipeline for genomic analysis of Acinetobacter baumannii. It integrates quality control, dual-scheme MLST, capsule typing, AMR detection, virulence and plasmid profiling, and critical-gene flagging into a single automated workflow. AcinetoScope wraps:

Quality control — FASTA validation with FastANI species confirmation against curated A. baumannii references
MLST — Multi-locus sequence typing, dual-scheme (Oxford: cpn60, fusA, gltA, pyrG, recA, rplB, rpoB; Pasteur) with IC1–IC12 assignment mlst (Seemann) + PubMLST
Capsule (K-locus) — K-type and OC-locus determination from the capsular polysaccharide biosynthesis locus Kaptive 3
AMR genes — Comprehensive resistance determinant detection AMRFinderPlus + ABRicate against CARD, ResFinder, NCBI, MEGARes 3.0, BacMet
Point mutations — Resistance-conferring point variants AMRFinderPlus
Virulence factors — VFDB gene screening ABRicate + VFDB
Plasmid profiling — Replicon detection using Acinetobacter-specific rep genes APT and PlasmidFinder
Critical gene flagging — Priority markers for infection control: carbapenemases, ESBLs, colistin and tigecycline resistance custom
Lineage catalogue — literature-curated International Clone reference custom

The AcinetoScope pipeline is open source and available on GitHub. The ABYSS website generator code is available at github.com/bbeckley-hub/abyss.

👥 The team

Brown Beckley

Lead Developer · Project Lead

Department of Medical Biochemistry,
University of Ghana Medical School
& Department of Biochemistry and Biotechnology, KNUST

✉️ Email 🐙 GitHub

Vincent Amarh

Co-Investigator

Department of Medical Biochemistry,
University of Ghana Medical School

✉️ Email

ABYSS is an independent, unfunded project born out of a need for open, accessible genomic surveillance tools in low- and middle-income settings. We welcome collaborations, bug reports, and feature suggestions.

⭐ Support ABYSS

ABYSS is an independent, unfunded project built on a shared HPC cluster and GitHub Pages. If you find it useful, there are three easy ways to help it reach more people.

⭐

Star the repo

A GitHub star helps other researchers discover ABYSS when they search for A. baumannii tooling.

⭐ Star on GitHub

📚

Cite us

Citations are the strongest signal that open resources deserve funding. Cite AcinetoScope and the tools you used in your Methods.

📚 See citation

🐛

Report & suggest

Found a call that doesn't match the literature? Want a new filter? Open an issue — every report improves the resource.

🐛 Open an issue

📚 Citation

🌊 Typing pipeline · AcinetoScope

Beckley B, Amarh V, Lopes BS, et al. AcinetoScope: a computational pipeline for rapid, comprehensive Acinetobacter baumannii outbreak investigation and resistance gene tracking. Scientific Reports. 2026.

DOI GitHub

📊 Gene data · Shelenkov et al.

Shelenkov A, Mikhaylova Y, Akimkin V. Genomic Epidemiology Dataset for the Important Nosocomial Pathogenic Bacterium Acinetobacter baumannii. Data. 2024;9(2):22.

DOI MDPI

The pipeline wraps several well-established community tools — mlst, Kaptive 3, AMRFinderPlus, ABRicate, APT, PlasmidFinder, and FastANI — and their reference databases.

Please also cite the specific tools you used in your Methods section, exactly as you would with any other bioinformatics pipeline. Key references include:

Seemann T. MLST: Scan contig files against PubMLST typing schemes. GitHub. 2018. GitHub
Jolley KA, Bray JE, Maiden MCJ. Open-access bacterial population genomics: BIGSdb, the PubMLST.org website and their applications. Wellcome Open Res. 2018;3:124. DOI
Stanton TD, Hetland MAK, Löhr IH, Holt KE, Wyres KL. Kaptive 3: Fast and Accurate in silico Antigen Typing with Kaptive 3. Microb Genom. 2025;11(6):001428. DOI
Lam MMC, Koong J, Holt KE, Hall RM, Hamidian M. Detection and Typing of Plasmids in Acinetobacter baumannii Using rep Genes. Microbiol Spectr. 2023;11(1):e0247822. DOI
Feldgarden M, et al. AMRFinderPlus and the Reference Gene Catalog. Sci Rep. 2021;11:12728. DOI
Seemann T. ABRicate: mass screening of contigs for antibiotic resistance genes. GitHub. 2024. GitHub
Jain C, et al. High throughput ANI analysis of 90K prokaryotic genomes reveals clear species boundaries. Nat Commun. 2018;9(1):5114. DOI
Alcock BP, et al. CARD 2023: expanded curation, support for machine learning, and resistome prediction. Nucleic Acids Res. 2023;51(D1):D690-D699. DOI
Bortolaia V, et al. ResFinder 4.0 for predictions of phenotypes from genotypes. J Antimicrob Chemother. 2020;75(12):3491-3500. DOI
Chen L, Zheng D, Liu B, Yang J, Jin Q. VFDB 2016: hierarchical and refined dataset for big data analysis. Nucleic Acids Res. 2016;44(D1):D694-D697. DOI
Bonin N, et al. MEGARes 3.0: a curated and updated database for AMR, biocide, and metal resistance gene detection. Nucleic Acids Res. 2023;51(D1):D677-D684. DOI
Gupta SK, et al. ARG-ANNOT: a new bioinformatic tool to discover antibiotic resistance genes. Antimicrob Agents Chemother. 2014;58(1):212-220. DOI
Pal C, et al. BacMet: antibacterial biocide and metal resistance genes database. Nucleic Acids Res. 2014;42:D737-D743. DOI
Cock PJ, et al. Biopython: freely available Python tools for computational molecular biology. Bioinformatics. 2009;25(11):1422-1423. DOI

For metadata provenance, cite NCBI BioSample and NCBI Assembly.

🙏 Acknowledgements

ABYSS would not be possible without the open-source community. We are deeply grateful to the developers, curators, and maintainers whose work is wrapped inside AcinetoScope and ABYSS:

Torsten Seemann — for mlst and ABRicate
Kelly Wyres, Ryan Wick, and the Kaptive team — for Kaptive 3 and the A. baumannii K-locus database
Ruth Hall, Mehrad Hamidian, and the APT team — for APT (Acinetobacter Plasmid Typing)
Center for Genomic Epidemiology (DTU) — for ResFinder
NCBI — for the datasets CLI, AMRFinderPlus, and the Assembly and BioSample databases
PubMLST & the Oxford MLST team — for allele and ST reference databases
The CARD, VFDB, MEGARes, ARG-ANNOT, and BacMet teams — for their reference databases
The open-source community — Python, Biopython, pandas, Chart.js, and every library we rely on

📬 Contact & contribute

Found a bug? Have a feature suggestion? Want to collaborate? We'd love to hear from you.

✉️ brownbeckley94@gmail.com 🐙 GitHub · Star the repo 🐛 Report an issue

ABYSS is released under the MIT License. You are free to use, modify, and redistribute it. Attribution is appreciated.