KEY RESOURCES TABLE.

REAGENT or RESOURCE	SOURCE	IDENTIFIER
Bacterial and virus strains
Acinetobacter baumannii	American Type Culture Collection	ATCC 19606
Escherichia coli	American Type Culture Collection	ATCC 11775
Escherichia coli	Escherichia coli MG1655 phnE_2::FRT	AIC221
Escherichia coli	Escherichia coli MG1655 pmrA53 phnE_2::FRT (polymyxin-resistant; colistin-resistant strain)	AIC222
Klebsiella pneumoniae	American Type Culture Collection	ATCC 13883
Pseudomonas aeruginosa		PA01
Pseudomonas aeruginosa		PA14
Staphylococcus aureus	American Type Culture Collection	ATCC 12600
Staphylococcus aureus	American Type Culture Collection	ATCC BAA-1556 (methicillin-resistant strain)
Akkermansia muciniphila	American Type Culture Collection	ATCC BAA-635
Bacteriodes fragilis	American Type Culture Collection	ATCC 25285
Bacteroides thetaiotaomicron	American Type Culture Collection	ATCC 29148
Bacteroides uniformis	American Type Culture Collection	ATCC 8492
Bacteroides vulgatus (Phocaeicola vulgatus)	American Type Culture Collection	ATCC 8482
Collinsella aerofaciens	American Type Culture Collection	ATCC 25986
Clostriudium scindens	American Type Culture Collection	ATCC 35704
Parabacteroides distasonis	American Type Culture Collection	ATCC 8503
Chemicals
Luria-Bertani broth	BD	244620
Tryptic soy broth	Sigma	T8907-1KG
Agar	Sigma	05039
MacConkey agar	RPI	M42560-500.0
Phosphate buffer saline	Sigma	P3913-10PAK
Glucose	Sigma	G5767
1-(N-phenylamino)naphthalene	Sigma	104043
3,3’-dipropylthiadicarbocyanine iodide	Sigma	43608
HEPES	Fisher	BP310-100
Potassium chloride (KCl)	Sigma	P3911
Deposited data
Code for generation of AMPSphere	This study	https://github.com/BigDataBiology/AMPsphere_manuscript
AMPSphere database	This study	https://zenodo.org/record/4606582
Software and algorithms
NGLess 1.3.0	Coelho et al.72	https://github.com/ngless-toolkit/ngless
JUG 2.1.1	Coelho73	https://github.com/luispedro/jug
Prodigal 2.6.3	Hyatt et al.32	https://github.com/hyattpd/Prodigal
Macrel v.1.0.0	Santos-Júnior et al.40	https://github.com/BigDataBiology/macrel
CDHit 4.8.1	Fu et al.74	https://github.com/weizhongli/cdhit
MMseqs2	Steinegger and Söding75	https://github.com/soedinglab/MMseqs2
python 3.8.2	Van Rossum76	https://www.python.org/
matplotlib 3.4.3	Hunter77	https://matplotlib.org/
numpy 1.21.2	Harris et al.78	https://numpy.org/
pandas 1.3.2	McKinney79	https://pandas.pydata.org/
plotly 5.2.1	Plotly Technologies Inc, 2015	https://plot.ly
scipy 1.7.1	Virtanen et al.80	https://www.scipy.org
scikit-learn 0.24	Pedregosa et al.81	https://scikit-learn.org/
scikit-bio 0.5.6	The scikit-bio development team, 202082	http://scikit-bio.org/
BioPython 1.7.9	Cock et al.83	https://biopython.org/
eggnog-mapper v2	Cantalapiedra et al.84	https://github.com/eggnogdb/eggnogmapper
HMMer 3.3+dfsg2-1	Eddy85	http://hmmer.org/
modlAMP 4.2.2	Müller et al.86	https://pypi.org/project/modlamp/
FastTree 2.1	Price et al.87	www.microbesonline.org/fasttree/
FastANI v.1.33	Jain et al.88	https://github.com/ParBLiSS/FastANI
Megahit 1.2.9	Li et al.89	https://github.com/voutcn/megahit/
Other
ProGenomes2	Mende et al.41	http://progenomes.embl.de/
DRAMP - Data repository of antimicrobial peptides 3.0	Shi et al.44	http://dramp.cpu-bioinfor.org/
UniprotKB 2021_03	The UniProt Consortium90	https://www.uniprot.org/
Eggnog v.5.0	Huerta-Cepas et al.48	http://eggnog5.embl.de/
SmProt database v.2.0	Hao et al.45	http://bigdata.ibp.ac.cn/SmProt/index.html
StarPep45k	Aguilera-Mendoza et al.91	http://mobiosd-hub.com/starpep
PFAM 34.0	Mistry et al.92	http://pfam.xfam.org/
AntiFAM v.6.0	Eberhardt et al.93	https://www.ebi.ac.uk/research/bateman/software/antifam-tool-identify-spurious-proteins
GTDB 07-RS95	Parks et al.55,56	https://gtdb.ecogenomic.org/
NCBI release 207	NCBI Resource Coordinators94	https://ftp.ncbi.nih.gov/refseq/release/
DBAASP	Pirtskhalava et al.58	https://dbaasp.org/home
APD3	Wang and Wang59	https://aps.unmc.edu/