Lacrimispora sphenoides (DSM 4024, VKM B-1591, 50)

Name: Lacrimispora sphenoides (DSM 4024, VKM B-1591, 50)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 11791

Type strain

Strain Designation 50

Culture col. no. DSM 4024 VKM B-1591 50

NCBI tax ID(s) 1298920 29370

Special Collections DSMZ

History DSMZ <- M. B. Vainstein, VKM; 50 <- G. I. Gogotova and M. B. Vainstein

Links

Lacrimispora sphenoides 50 is an anaerobe bacterium that was isolated from freshwater mud.

anaerobe genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 47791

DSM 4024,VKM B-1591

@ref 20215

Last LPSN update 2026-05-29 08:27:38

Domain Bacteria

Phylum Bacillota

Class Clostridia

Order Eubacteriales

Family Lachnospiraceae

Genus Lacrimispora

Species Lacrimispora sphenoides

Full scientific name Lacrimispora sphenoides (Douglas et al. 1919) Haas and Blanchard 2020

Synonyms (3)

Clostridium sphenoides
"Bacillus sphenoides"
Desulfotomaculum guttoideum

BacDive ID	Other strains from **Lacrimispora sphenoides** (4)	Type strain
2704	L. sphenoides Thorlby, Tholby, 10086, DSM 632, ATCC 19403, ... (type strain)
2703	L. sphenoides C2, DSM 614
2705	L. sphenoides DSM 1225, UQM 780
158918	L. sphenoides H1_31, DSM 108199

Morphology

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
1576	PY + X MEDIUM (DSMZ Medium 104b)		Medium recipe at MediaDive	Name: PY + X MEDIUM (DSMZ Medium 104b) Composition: Yeast extract 10.0 g/l D-Glucose 5.0 g/l Trypticase peptone 5.0 g/l Meat peptone 5.0 g/l L-Cysteine HCl x H2O 0.5 g/l NaHCO3 0.4 g/l NaCl 0.08 g/l KH2PO4 0.04 g/l K2HPO4 0.04 g/l MgSO4 x 7 H2O 0.02 g/l CaCl2 x 2 H2O 0.01 g/l Sodium resazurin 0.0005 g/l Distilled water
1576	DESULFOVIBRIO (POSTGATE) MEDIUM (DSMZ Medium 63)		Medium recipe at MediaDive	Name: DESULFOVIBRIO (POSTGATE) MEDIUM (DSMZ Medium 63) Composition: MgSO4 x 7 H2O 2.0 g/l Na-DL-lactate 2.0 g/l NH4Cl 1.0 g/l Yeast extract 1.0 g/l Na2SO4 1.0 g/l FeSO4 x 7 H2O 0.5 g/l K2HPO4 0.5 g/l CaCl2 x 2 H2O 0.1 g/l Na-thioglycolate 0.1 g/l Ascorbic acid 0.1 g/l Sodium resazurin 0.0005 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)
1576	positive	growth	30

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
1576	anaerobe
125438	anaerobe	91.386
125439	facultative anaerobe	98.102

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Environmental	#Aquatic	#Freshwater
#Environmental	#Terrestrial	#Mud (Sludge)

Isolation

@ref	Sample type	Geographic location	Country	Continent
1576	freshwater mud	Kuban river	USSR	Asia

Taxonmaps

69479

Global distribution of 16S sequence Y11568 (>99% sequence identity) for Lacrimispora from Microbeatlas

Aquatic Samples	2526
Soil Samples	3355
Animal Samples	19545
Plant Samples	988
Total Samples	26414

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
1576	1	Risk group (German classification) According to TRBA 466

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	IMG-taxon 2687453780 annotated assembly for Lacrimispora sphenoides DSM 4024	contig	GCA_900105215	58134.4	2687453780	29370	77.07
66792	Desulfotomaculum guttoideum DSM 4024	contig		1298920.3		1298920	75.6

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
1576	D.guttoideum 16S rRNA gene	Y11568	1495		58134
124043	Lacrimispora sphenoides strain DSM 4024 16S ribosomal RNA gene, partial sequence.	MZ056865	1402		29370

GC content

@ref	GC-content (mol%)	Method
1576	43.4	sequence analysis

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: IMG-taxon 2687453780 annotated assembly for Lacrimispora sphenoides DSM 4024
BV-BRC: 58134.4

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	oxygen_tolerance	BacteriaNetⓘ	facultative anaerobe	98.10	no
125439	motility	BacteriaNetⓘ	yes	80.07	no
125439	gram_stain	BacteriaNetⓘ	variable	52.89	no
125439	spore_formation	BacteriaNetⓘ	yes	89.13	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: [Desulfotomaculum] guttoideum strain DSM 4024
PATRIC: 58134.4

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	59.70	no
125438	anaerobic	anaerobicⓘ	yes	91.39	yes
125438	spore-forming	spore-formingⓘ	yes	69.65	no
125438	aerobic	aerobicⓘ	no	93.57	yes
125438	thermophilic	thermophileⓘ	no	93.18	yes
125438	flagellated	motile2+ⓘ	yes	75.51	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Phylogeny	Reclassification of the Clostridium clostridioforme and Clostridium sphenoides clades as Enterocloster gen. nov. and Lacrimispora gen. nov., including reclassification of 15 taxa.	Haas KN, Blanchard JL.	Int J Syst Evol Microbiol	10.1099/ijsem.0.003698	2020
	Effect of loading rate and pH on glycerol fermentation and microbial population in an upflow anaerobic filter reactor.	Cordeiro CN, Rojas P, Veras STS, Kato MT, Florencio L, Sanz JL.	Bioprocess Biosyst Eng	10.1007/s00449-024-03003-6	2024
	A cross-cohort study identifies potential oral microbial markers for esophageal squamous cell carcinoma.	Yu Y, Xia L, Wang Z, Zhu T, Zhao L, Fan S.	iScience	10.1016/j.isci.2024.111453	2024
	Alterations in lung and gut microbiota reduce diversity in patients with nontuberculous mycobacterial pulmonary disease.	Choi JY, Shim B, Park Y, Kang YA.	Korean J Intern Med	10.3904/kjim.2023.097	2023
Genetics	Tartrate fermentation with H₂ production by a new member of Sporomusaceae enriched from rice paddy soil.	Pereira-Mora L, Guerrero LD, Erijman L, Fernandez-Scavino A.	Appl Environ Microbiol	10.1128/aem.02351-23	2024
	Microbiome analysis revealing microbial interactions and secondary bacterial infections in COVID-19 patients comorbidly affected by Type 2 diabetes.	Al-Emran HM, Rahman S, Hasan MS, Ul Alam R, Islam OK, Anwar A, Jahid MIK, Hossain A.	J Med Virol	10.1002/jmv.28234	2023
	Induction of mastitis by cow-to-mouse fecal and milk microbiota transplantation causes microbiome dysbiosis and genomic functional perturbation in mice.	Hoque MN, Rahman MS, Islam T, Sultana M, Crandall KA, Hossain MA.	Anim Microbiome	10.1186/s42523-022-00193-w	2022
	Update on Accepted Novel Bacterial Isolates Derived from Human Clinical Specimens and Taxonomic Revisions Published in 2020 and 2021.	Munson E, Carroll KC.	J Clin Microbiol	10.1128/jcm.00282-22	2023
	Enterocloster alcoholdehydrogenati sp. nov., a Novel Bacterial Species Isolated from the Feces of a Patient with Alcoholism.	Oikawa D, Fukui K, Aoki Y, Waki T, Takahashi S, Shimoyama T, Nakayama T.	Curr Microbiol	10.1007/s00284-023-03285-1	2023
	Lacrimispora sanguinis sp. nov., isolated from human blood.	Yu HJ, Cho YY, Paek J, Kang M, Ahn MY, Kim H, Byun JH, Kim TY, Huh HJ, Bai L, Chang YH.	PLoS One	10.1371/journal.pone.0334875	2025
Biotechnology	Lacrimispora sinapis sp. nov., isolated from pickled potherb mustard (Brassica juncea Coss.).	Ren Q, Wang D, Han J, Liu Z, Wu Z.	Int J Syst Evol Microbiol	10.1099/ijsem.0.006675	2025
Phylogeny	Lacrimispora brassicae sp. nov. isolated from fermented cabbage, and proposal of Clostridium indicum Gundawar et al. 2019 and Clostridium methoxybenzovorans Mechichi et al. 1999 as heterotypic synonyms of Lacrimispora amygdalina (Parshina et al. 2003) Haas and Blanchard 2020 and Lacrimispora indolis (McClung and McCoy 1957) Haas and Blanchard 2020, respectively.	Kobayashi H, Tanizawa Y, Sakamoto M, Ohkuma M, Tohno M.	Int J Syst Evol Microbiol	10.1099/ijsem.0.006456	2024

References

#1576	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 4024
#20215	Parte, A.C., Sardà Carbasse, J., Meier-Kolthoff, J.P., Reimer, L.C. and Göker, M.: List of Prokaryotic names with Standing in Nomenclature (LPSN) moves to the DSMZ. IJSEM ( DOI 10.1099/ijsem.0.004332 )
#66792	Julia Koblitz, Joaquim Sardà, Lorenz Christian Reimer, Boyke Bunk, Jörg Overmann: Automatically annotated for the DiASPora project (Digital Approaches for the Synthesis of Poorly Accessible Biodiversity Information) .
#69479	João F Matias Rodrigues, Janko Tackmann,Gregor Rot, Thomas SB Schmidt, Lukas Malfertheiner, Mihai Danaila,Marija Dmitrijeva, Daniela Gaio, Nicolas Näpflin and Christian von Mering. University of Zurich.: MicrobeAtlas 1.0 beta .
#124043	Isabel Schober, Julia Koblitz: Data extracted from sequence databases, automatically matched based on designation and taxonomy .
#125438	Julia Koblitz, Lorenz Christian Reimer, Rüdiger Pukall, Jörg Overmann: Predicting bacterial phenotypic traits through improved machine learning using high-quality, curated datasets. 2024 ( DOI 10.1101/2024.08.12.607695 )
#125439	Philipp Münch, René Mreches, Martin Binder, Hüseyin Anil Gündüz, Xiao-Yin To, Alice McHardy: deepG: Deep Learning for Genome Sequence Data. R package version 0.3.1 .
#126262	A. Lissin, I. Schober, J. F. Witte, H. Lüken, A. Podstawka, J. Koblitz, B. Bunk, P. Dawyndt, P. Vandamme, P. de Vos, J. Overmann, L. C. Reimer: StrainInfo—the central database for linked microbial strain identifiers. ( DOI 10.1093/database/baaf059 )

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Lacrimispora sphenoides (DSM 4024, VKM B-1591, 50)

Name and taxonomic classification

Morphology

Culture and growth conditions

Culture medium

Culture temp

Physiology and metabolism

Oxygen tolerance

Isolation, sampling and environmental information

Isolation source categories

Isolation

Taxonmaps

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_900105215

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

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