The emergence of interstellar molecular complexity explained by interacting networks.

Recent years have witnessed the detection of an increasing number of complex organic molecules in interstellar space, some of them being of prebiotic interest. Disentangling the origin of interstellar prebiotic chemistry and its connection to biochemistry and ultimately, to biology is an enormously challenging scientific goal where the application of complexity theory and network science has not been fully exploited. Encouraged by this idea, we present a theoretical and computational framework to model the evolution of simple networked structures toward complexity. In our environment, complex networks represent simplified chemical compounds and interact optimizing the dynamical importance of their nodes. We describe the emergence of a transition from simple networks toward complexity when the parameter representing the environment reaches a critical value. Notably, although our system does not attempt to model the rules of real chemistry nor is dependent on external input data, the results describe the emergence of complexity in the evolution of chemical diversity in the interstellar medium. Furthermore, they reveal an as yet unknown relationship between the abundances of molecules in dark clouds and the potential number of chemical reactions that yield them as products, supporting the ability of the conceptual framework presented here to shed light on real scenarios. Our work reinforces the notion that some of the properties that condition the extremely complex journey from the chemistry in space to prebiotic chemistry and finally, to life could show relatively simple and universal patterns.

Coupled C, H, N, S and Fe biogeochemical cycles operating in the continental deep subsurface of the Iberian Pyrite Belt.

Microbial activity is a major contributor to the biogeochemical cycles that make up the life support system of planet Earth. A 613 m deep geomicrobiological perforation and a systematic multi-analytical characterization revealed an unexpected diversity associated with the rock matrix microbiome that operates in the subsurface of the Iberian Pyrite Belt (IPB). Members of 1 class and 16 genera were deemed the most representative microorganisms of the IPB deep subsurface and selected for a deeper analysis. The use of fluorescence in situ hybridization allowed not only the identification of microorganisms but also the detection of novel activities in the subsurface such as anaerobic ammonium oxidation (ANAMMOX) and anaerobic methane oxidation, the co-occurrence of microorganisms able to maintain complementary metabolic activities and the existence of biofilms. The use of enrichment cultures sensed the presence of five different complementary metabolic activities along the length of the borehole and isolated 29 bacterial species. Genomic analysis of nine isolates identified the genes involved in the complete operation of the light-independent coupled C, H, N, S and Fe biogeochemical cycles. This study revealed the importance of nitrate reduction microorganisms in the oxidation of iron in the anoxic conditions existing in the subsurface of the IPB.

Immunoanalytical Approach for Detecting and Identifying Ancestral Peptide Biomarkers in Early Earth Analogue Environments.

Several mass spectrometry and spectroscopic techniques have been used in the search for molecular biomarkers on Mars. A major constraint is their capability to detect and identify large and complex compounds such as peptides or other biopolymers. Multiplex immunoassays can detect these compounds, but antibodies must be produced for a large number of sequence-dependent molecular targets. Ancestral Sequence Reconstruction (ASR) followed by protein "resurrection" in the lab can help to narrow the selection of targets. Herein, we propose an immunoanalytical method to identify ancient and universally conserved protein/peptide sequences as targets for identifying ancestral biomarkers in nature. We have developed, tested, and validated this approach by producing antibodies to eight previously described ancestral resurrected proteins (three ß-lactamases, three thioredoxins, one Elongation Factor Tu, and one RuBisCO, all of them theoretically dated as Precambrian), and used them as a proxy to search for any potential feature of them that could be present in current natural environments. By fluorescent sandwich microarray immunoassays (FSMI), we have detected positive immunoreactions with antibodies to the oldest ß-lactamase and thioredoxin proteins (ca. 4 Ga) in samples from a hydrothermal environment. Fine epitope mapping and inhibitory immunoassays allowed the identification of well-conserved epitope peptide sequences that resulted from ASR and were present in the sample. We corroborated these results by metagenomic sequencing and found several genes encoding analogue proteins with significant matches to the peptide epitopes identified with the antibodies. The results demonstrated that peptides inferred from ASR studies have true counterpart analogues in Nature, which validates and strengthens the well-known ASR/protein resurrection technique and our immunoanalytical approach for investigating ancient environments and metabolisms on Earth and elsewhere.

M&Ms: a versatile software for building microbial mock communities.

SUMMARY: Advances in sequencing technologies have triggered the development of many bioinformatic tools aimed to analyze 16S rDNA sequencing data. As these tools need to be tested, it is important to simulate datasets that resemble samples from different environments. Here, we introduce M&Ms, a user-friendly open-source bioinformatic tool to produce different 16S rDNA datasets from reference sequences, based on pragmatic ecological parameters. It creates sequence libraries for 'in silico' microbial communities with user-controlled richness, evenness, microdiversity and source environment. M&Ms allows the user to generate simple to complex read datasets based on real parameters that can be used in developing bioinformatic software or in benchmarking current tools. AVAILABILITY AND IMPLEMENTATION: The source code of M&Ms is freely available at https://github.com/ggnatalia/MMs (GPL-3.0 License). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Metagenomic and metabolic analyses of poly-extreme microbiome from an active crater volcano lake.

El Chichón volcano is one of the most active volcanoes in Mexico. Previous studies have described its poly-extreme conditions and its bacterial composition, although the functional features of the complete microbiome have not been characterized yet. By using metabarcoding analysis, metagenomics, metabolomics and enzymology techniques, the microbiome of the crater lake was characterized in this study. New information is provided on the taxonomic and functional diversity of the representative Archaea phyla, Crenarchaeota and Euryarchaeota, as well as those that are representative of Bacteria, Thermotogales and Aquificae. With culture of microbial consortia and with the genetic information collected from the natural environment sampling, metabolic interactions were identified between prokaryotes, which can withstand multiple extreme conditions. The existence of a close relationship between the biogeochemical cycles of carbon and sulfur in an active volcano has been proposed, while the relationship in the energy metabolism of thermoacidophilic bacteria and archaea in this multi-extreme environment was biochemically revealed for the first time. These findings contribute towards understanding microbial metabolism under extreme conditions, and provide potential knowledge pertaining to "microbial dark matter", which can be applied to biotechnological processes and evolutionary studies.

Temperature and elemental sulfur shape microbial communities in two extremely acidic aquatic volcanic environments.

Aquatic environments of volcanic origin provide an exceptional opportunity to study the adaptations of microorganisms to early planet life conditions. Here, we characterized the prokaryotic communities and physicochemical properties of seepage sites at the bottom of the Poas Volcano crater and the Agrio River, two geologically related extremely acidic environments located in Costa Rica. Both locations hold a low pH (1.79-2.20) and have high sulfate and iron concentrations (Fe = 47-206 mg/L, SO42- = 1170-2460 mg/L), but significant differences in their temperature (90.0-95.0 ºC in the seepages at Poas Volcano, 19.1-26.6 ºC in Agrio River) and in the elemental sulfur content. Based on the analysis of 16S rRNA gene sequences, we determined that Sulfobacillus spp. represented more than half of the sequences in Poas Volcano seepage sites, while Agrio River was dominated by Leptospirillum and members of the archaeal order Thermoplasmatales. Both environments share some chemical characteristics and part of their microbiota, however, the temperature and the reduced sulfur are likely the main distinguishing features, ultimately shaping their microbial communities. Our data suggest that in the Poas Volcano-Agrio River system there is a common metabolism but with specialization of species that adapt to the physicochemical conditions of each environment.

Viable cyanobacteria in the deep continental subsurface.

Cyanobacteria are ecologically versatile microorganisms inhabiting most environments, ranging from marine systems to arid deserts. Although they possess several pathways for light-independent energy generation, until now their ecological range appeared to be restricted to environments with at least occasional exposure to sunlight. Here we present molecular, microscopic, and metagenomic evidence that cyanobacteria predominate in deep subsurface rock samples from the Iberian Pyrite Belt Mars analog (southwestern Spain). Metagenomics showed the potential for a hydrogen-based lithoautotrophic cyanobacterial metabolism. Collectively, our results suggest that they may play an important role as primary producers within the deep-Earth biosphere. Our description of this previously unknown ecological niche for cyanobacteria paves the way for models on their origin and evolution, as well as on their potential presence in current or primitive biospheres in other planetary bodies, and on the extant, primitive, and putative extraterrestrial biospheres.

A dimensional reduction approach to modulate the core ruminal microbiome associated with methane emissions via selective breeding.

The rumen is a complex microbial system of substantial importance in terms of greenhouse gas emissions and feed efficiency. This study proposes combining metagenomic and host genomic data for selective breeding of the cow hologenome toward reduced methane emissions. We analyzed nanopore long reads from the rumen metagenome of 437 Holstein cows from 14 commercial herds in 4 northern regions in Spain. After filtering, data were treated as compositional. The large complexity of the rumen microbiota was aggregated, through principal component analysis (PCA), into few principal components (PC) that were used as proxies of the core metagenome. The PCA allowed us to condense the huge and fuzzy taxonomical and functional information from the metagenome into a few PC. Bivariate animal models were applied using these PC and methane production as phenotypes. The variability condensed in these PC is controlled by the cow genome, with heritability estimates for the first PC of ~0.30 at all taxonomic levels, with a large probability (>83%) of the posterior distribution being >0.20 and with the 95% highest posterior density interval (95%HPD) not containing zero. Most genetic correlation estimates between PC1 and methane were large (≥0.70), with most of the posterior distribution (>82%) being >0.50 and with its 95%HPD not containing zero. Enteric methane production was positively associated with relative abundance of eukaryotes (protozoa and fungi) through the first component of the PCA at phylum, class, order, family, and genus. Nanopore long reads allowed the characterization of the core rumen metagenome using whole-metagenome sequencing, and the purposed aggregated variables could be used in animal breeding programs to reduce methane emissions in future generations.

SQMtools: automated processing and visual analysis of 'omics data with R and anvi'o.

BACKGROUND: The dramatic decrease in sequencing costs over the last decade has boosted the adoption of high-throughput sequencing applications as a standard tool for the analysis of environmental microbial communities. Nowadays even small research groups can easily obtain raw sequencing data. After that, however, non-specialists are faced with the double challenge of choosing among an ever-increasing array of analysis methodologies, and navigating the vast amounts of results returned by these approaches. RESULTS: Here we present a workflow that relies on the SqueezeMeta software for the automated processing of raw reads into annotated contigs and reconstructed genomes (bins). A set of custom scripts seamlessly integrates the output into the anvi'o analysis platform, allowing filtering and visual exploration of the results. Furthermore, we provide a software package with utility functions to expose the SqueezeMeta results to the R analysis environment. CONCLUSIONS: Altogether, our workflow allows non-expert users to go from raw sequencing reads to custom plots with only a few powerful, flexible and well-documented commands.

Microbial Community Structure Along a Horizontal Oxygen Gradient in a Costa Rican Volcanic Influenced Acid Rock Drainage System.

We describe the geochemistry and microbial diversity of a pristine environment that resembles an acid rock drainage (ARD) but it is actually the result of hydrothermal and volcanic influences. We designate this environment, and other comparable sites, as volcanic influenced acid rock drainage (VARD) systems. The metal content and sulfuric acid in this ecosystem stem from the volcanic milieu and not from the product of pyrite oxidation. Based on the analysis of 16S rRNA gene amplicons, we report the microbial community structure in the pristine San Cayetano Costa Rican VARD environment (pH = 2.94-3.06, sulfate ~ 0.87-1.19 g L-1, iron ~ 35-61 mg L-1 (waters), and ~ 8-293 g kg-1 (sediments)). San Cayetano was found to be dominated by microorganisms involved in the geochemical cycling of iron, sulfur, and nitrogen; however, the identity and abundance of the species changed with the oxygen content (0.40-6.06 mg L-1) along the river course. The hypoxic source of San Cayetano is dominated by a putative anaerobic sulfate-reducing Deltaproteobacterium. Sulfur-oxidizing bacteria such as Acidithiobacillus or Sulfobacillus are found in smaller proportions with respect to typical ARD. In the oxic downstream, we identified aerobic iron-oxidizers (Leptospirillum, Acidithrix, Ferrovum) and heterotrophic bacteria (Burkholderiaceae bacterium, Trichococcus, Acidocella). Thermoplasmatales archaea closely related to environmental phylotypes found in other ARD niches were also observed throughout the entire ecosystem. Overall, our study shows the differences and similarities in the diversity and distribution of the microbial communities between an ARD and a VARD system at the source and along the oxygen gradient that establishes on the course of the river.

Microbiota characterization of sheep milk and its association with somatic cell count using 16s rRNA gene sequencing.

This work aimed to use 16S ribosomal RNA sequencing with the Illumina MiSeq platform to describe the milk microbiota from 50 healthy Assaf ewes. The global observed microbial community for clinically healthy milk samples analysed was complex and showed a vast diversity. The core microbiota of the sheep milk includes five genera: Staphylococcus, Lactobacillus, Corynebacterium, Streptococcus and Escherichia/Shigella. Although there are some differences, some of these genera are common with the microbiota core pattern of milk from other species, especially with dairy cows. The microbial composition of the studied samples, based on the definition of amplicon sequence variants, was analysed through a correlation network. A preliminary analysis by grouping the milk samples based on their somatic cell count (SCC), which is considered an indicator of subclinical mastitis (SM), showed certain differences for the core of the samples identified as SM. The differences in the microbiota diversity pattern among samples might also suggest that subclinical mastitis would be associated with the significant increase in some genera that are inhabitants of the mammary gland and a remarkable concomitant reduction in the microbial diversity. Additionally, we have also presented here a preliminary analysis to assess the impact of the sheep milk microbiome on SCC, as an indicator of subclinical mastitis. The results here reported provide a first characterization of the sheep milk microbiota and settle the basis for future studies in this field.

Assessing the performance of different approaches for functional and taxonomic annotation of metagenomes.

BACKGROUND: Metagenomes can be analysed using different approaches and tools. One of the most important distinctions is the way to perform taxonomic and functional assignment, choosing between the use of assembly algorithms or the direct analysis of raw sequence reads instead by homology searching, k-mer analysys, or detection of marker genes. Many instances of each approach can be found in the literature, but to the best of our knowledge no evaluation of their different performances has been carried on, and we question if their results are comparable. RESULTS: We have analysed several real and mock metagenomes using different methodologies and tools, and compared the resulting taxonomic and functional profiles. Our results show that database completeness (the representation of diverse organisms and taxa in it) is the main factor determining the performance of the methods relying on direct read assignment either by homology, k-mer composition or similarity to marker genes, while methods relying on assembly and assignment of predicted genes are most influenced by metagenomic size, that in turn determines the completeness of the assembly (the percentage of read that were assembled). CONCLUSIONS: Although differences exist, taxonomic profiles are rather similar between raw read assignment and assembly assignment methods, while they are more divergent for methods based on k-mers and marker genes. Regarding functional annotation, analysis of raw reads retrieves more functions, but it also makes a substantial number of over-predictions. Assembly methods are more advantageous as the size of the metagenome grows bigger.

Mycobiome Profiles in Breast Milk from Healthy Women Depend on Mode of Delivery, Geographic Location, and Interaction with Bacteria.

Recent studies report the presence of fungal species in breast milk of healthy mothers, suggesting a potential role in infant mycobiome development. In the present work, we aimed to determine whether the healthy human breast milk mycobiota is influenced by geographical location and mode of delivery, as well as to investigate its interaction with bacterial profiles in the same samples. A total of 80 mature breast milk samples from 4 different countries were analyzed by Illumina sequencing of the internal transcribed spacer 1 (ITS1) region, joining the 18S and 5.8S regions of the fungal rRNA region. Basidiomycota and Ascomycota were found to be the dominant phyla, with Malassezia and Davidiella being the most prevalent genera across countries. A core formed by Malassezia, Davidiella, Sistotrema, and Penicillium was shared in the milk samples from the different origins, although specific shifts in mycobiome composition were associated with geographic location and delivery mode. The presence of fungi in the breast milk samples was further confirmed by culture and isolate characterization, and fungal loads were estimated by quantitative PCR (qPCR) targeting the fungal ITS1 region. Cooccurrence network analysis of bacteria and fungi showed complex interactions that were influenced by geographical location, mode of delivery, maternal age, and pregestational body mass index. The presence of a breast milk mycobiome was confirmed in all samples analyzed, regardless of the geographic origin.IMPORTANCE During recent years, human breast milk has been documented as a potential source of bacteria for the newborn. Recently, we have reported the presence of fungi in breast milk from healthy mothers. It is well known that environmental and perinatal factors can affect milk bacteria; however, the impact on milk fungi is still unknown. The current report describes fungal communities (mycobiota) in breast milk samples across different geographic locations and the influence of the mode of delivery. We also provide novel insights on bacterium-fungus interactions, taking into account environmental and perinatal factors. We identified a core of four genera shared across locations, consisting of Malassezia, Davidiella, Sistotrema, and Penicillium, which have been reported to be present in the infant gut. Our data confirm the presence of fungi in breast milk across continents and support the potential role of breast milk in the initial seeding of fungal species in the infant gut.

Thermoplasmatales and sulfur-oxidizing bacteria dominate the microbial community at the surface water of a CO2-rich hydrothermal spring located in Tenorio Volcano National Park, Costa Rica.

Here we report the chemical and microbial characterization of the surface water of a CO2-rich hydrothermal vent known in Costa Rica as Borbollones, located at Tenorio Volcano National Park. The Borbollones showed a temperature surrounding 60 °C, a pH of 2.4 and the gas released has a composition of ~ 97% CO2, ~ 0.07% H2S, ~ 2.3% N2 and ~ 0.12% CH4. Other chemical species such as sulfate and iron were found at high levels with respect to typical fresh water bodies. Analysis by 16S rRNA gene metabarcoding revealed that in Borbollones predominates an archaeon from the order Thermoplasmatales and one bacterium from the genus Sulfurimonas. Other sulfur- (genera Thiomonas, Acidithiobacillus, Sulfuriferula, and Sulfuricurvum) and iron-oxidizing bacteria (genera Sideroxydans, Gallionella, and Ferrovum) were identified. Our results show that CO2-influenced surface water of Borbollones contains microorganisms that are usually found in acid rock drainage environments or sulfur-rich hydrothermal vents. To our knowledge, this is the first microbiological characterization of a CO2-dominated hydrothermal spring from Central America and expands our understanding of those extreme ecosystems.

A novel conceptual approach to read-filtering in high-throughput amplicon sequencing studies.

Adequate read filtering is critical when processing high-throughput data in marker-gene-based studies. Sequencing errors can cause the mis-clustering of otherwise similar reads, artificially increasing the number of retrieved Operational Taxonomic Units (OTUs) and therefore leading to the overestimation of microbial diversity. Sequencing errors will also result in OTUs that are not accurate reconstructions of the original biological sequences. Herein we present the Poisson binomial filtering algorithm (PBF), which minimizes both problems by calculating the error-probability distribution of a sequence from its quality scores. In order to validate our method, we quality-filtered 37 publicly available datasets obtained by sequencing mock and environmental microbial communities with the Roche 454, Illumina MiSeq and IonTorrent PGM platforms, and compared our results to those obtained with previous approaches such as the ones included in mothur, QIIME and USEARCH. Our algorithm retained substantially more reads than its predecessors, while resulting in fewer and more accurate OTUs. This improved sensitiveness produced more faithful representations, both quantitatively and qualitatively, of the true microbial diversity present in the studied samples. Furthermore, the method introduced in this work is computationally inexpensive and can be readily applied in conjunction with any existent analysis pipeline.

Pristine but metal-rich Río Sucio (Dirty River) is dominated by Gallionella and other iron-sulfur oxidizing microbes.

Whether the extreme conditions of acidity and heavy metal pollution of streams and rivers originating in pyritic formations are caused primarily by mining activities or by natural activities of metal-oxidizing microbes living within the geological formations is a subject of considerable controversy. Most microbiological studies of such waters have so far focused on acid mine drainage sites, which are heavily human-impacted environments, so it has been problematic to eliminate the human factor in the question of the origin of the key metal compounds. We have studied the physico-chemistry and microbiology of the Río Sucio in the Braulio Carrillo National Park of Costa Rica, 22 km from its volcanic rock origin. Neither the remote origin, nor the length of the river to the sampling site, have experienced human activity and are thus pristine. The river water had a characteristic brownish-yellow color due to high iron-dominated minerals, was slightly acidic, and rich in chemolithoautotrophic iron- and sulfur-oxidizing bacteria, dominated by Gallionella spp. Río Sucio is thus a natural acid-rock drainage system whose metal-containing components are derived primarily from microbial activities.

Horizontal Gene Transfer of Phytochelatin Synthases from Bacteria to Extremophilic Green Algae.

Transcriptomic sequencing together with bioinformatic analyses and an automated annotation process led us to identify novel phytochelatin synthase (PCS) genes from two extremophilic green algae (Chlamydomonas acidophila and Dunaliella acidophila). These genes are of intermediate length compared to known PCS genes from eukaryotes and PCS-like genes from prokaryotes. A detailed phylogenetic analysis gives new insight into the complicated evolutionary history of PCS genes and provides evidence for multiple horizontal gene transfer events from bacteria to eukaryotes within the gene family. A separate subgroup containing PCS-like genes within the PCS gene family is not supported since the PCS genes are monophyletic only when the PCS-like genes are included. The presence and functionality of the novel genes in the organisms were verified by genomic sequencing and qRT-PCR. Furthermore, the novel PCS gene in Chlamydomonas acidophila showed very strong induction by cadmium. Cloning and expression of the gene in Escherichia coli clearly improves its cadmium resistance. The gene in Dunaliella was not induced, most likely due to gene duplication.

Comparative Transcriptomic Analysis of the Response of Dunaliella acidophila (Chlorophyta) to Short-Term Cadmium and Chronic Natural Metal-Rich Water Exposures.

Heavy metals are toxic compounds known to cause multiple and severe cellular damage. However, acidophilic extremophiles are able to cope with very high concentrations of heavy metals. This study investigated the stress response under natural environmental heavy metal concentrations in an acidophilic Dunaliella acidophila. We employed Illumina sequencing for a de novo transcriptome assembly and to identify changes in response to high cadmium concentrations and natural metal-rich water. The photosynthetic performance was also estimated by pulse amplitude-modulated (PAM) fluorescence. Transcriptomic analysis highlights a number of processes mainly related to a high constitutive expression of genes involved in oxidative stress and response to reactive oxygen species (ROS), even in the absence of heavy metals. Photosynthetic activity seems to be unaltered under short-term exposition to Cd and chronic exposure to natural metal-rich water, probably due to an increase in the synthesis of structural photosynthetic components preserving their functional integrity. An overrepresentation of Gene Ontology (GO) terms related to metabolic activities, transcription, and proteosomal catabolic process was observed when D. acidophila grew under chronic exposure to natural metal-rich water. GO terms involved in carbohydrate metabolic process, reticulum endoplasmic and Golgi bodies, were also specifically overrepresented in natural metal-rich water library suggesting an endoplasmic reticulum stress response.

Transcriptional response to copper excess and identification of genes involved in heavy metal tolerance in the extremophilic microalga Chlamydomonas acidophila.

High concentrations of heavy metals are typical of acidic environments. Therefore, studies on acidophilic organisms in their natural environments improve our understanding on the evolution of heavy metal tolerance and detoxification in plants. Here we sequenced the transcriptome of the extremophilic microalga Chlamydomonas acidophila cultivated in control conditions and with 500 µM of copper for 24 h. High-throughput 454 sequencing was followed by de novo transcriptome assembly. The reference transcriptome was annotated and genes related to heavy metal tolerance and abiotic stress were identified. Analyses of differentially expressed transcripts were used to detect genes involved in metabolic pathways related to abiotic stress tolerance, focusing on effects caused by increased levels of copper. Both transcriptomic data and observations from PAM fluorometry analysis suggested that the photosynthetic activity of C. acidophila is not adversely affected by addition of high amounts of copper. Up-regulated transcripts include several transcripts related to photosynthesis and carbohydrate metabolism, transcripts coding for general stress response, and a transcript annotated as homologous to the oil-body-associated protein HOGP coding gene. The first de novo assembly of C. acidophila significantly increases transcriptomic data available on extremophiles and green algae and thus provides an important reference for further molecular genetic studies. The differences between differentially expressed transcripts detected in our study suggest that the response to heavy metal exposure in C. acidophila is different from other studied green algae.

Tessaracoccus lapidicaptus sp. nov., an actinobacterium isolated from the deep subsurface of the Iberian pyrite belt.

A novel actinobacterium, designated IPBSL-7(T), was isolated from a drilling core 297 m deep obtained from the Iberian Pyrite Belt. The strain was isolated anaerobically using nitrate as the electron acceptor. 16S rRNA gene sequence analysis revealed that it was related to Tessaracoccus flavescens SST-39(T) (95.7% similarity), Tessaracoccus bendigoensis Ben 106(T) (95.7%), Tessaracoccus lubricantis KSS-17Se(T) (95.6%) and Tessaracoccus oleiagri SL014B-20A1(T) (95.0%), while its similarity to any other member of the family Propionibacteriaceae was less than 94%. Cells were non-motile, non-spore-forming, Gram-positive, oval to rod-shaped, and often appeared in pairs or small groups. The strain was facultatively anaerobic, oxidase-negative, catalase-positive and capable of reducing nitrate. Colonies were circular, convex, smooth and colourless. The organism could grow at between 15 and 40 °C, with an optimal growth at 37 °C. The pH range for growth was from pH 6 to 9, with pH 8 being the optimal value. Strain IPBSL-7(T) had peptidoglycan type A3-γ', with ll-diaminopimelic acid as the diagnostic diamino-acid and glycine at position 1 of the peptide subunit. The dominant menaquinone was MK-9(H4) (93.8%). The major cellular fatty acid was anteiso-C15:0 (55.0%). The DNA G+C content was 70.3 mol%. On the basis of phenotypic and phylogenetic results, strain IPBSL-7(T) can be differentiated from previously described species of the genus Tessaracoccus and, therefore, represents a novel species, for which the name Tessaracoccus lapidicaptus sp. nov. is proposed. The type strain is IPBSL-7(T) ( = CECT 8385(T) = DSM 27266(T)).