The impact of respiratory infections and probiotic use on the nasal microbiota of frail residents in long-term care homes.

Background: Residents in long-term care homes, who tend to be of advanced age and frail, are at increased risk of respiratory infections. The respiratory microbiota is known to change with age, but whether these changes contribute to the risk of infection is not known. Our goal was to determine how the nasal microbiota of frail older adults changes during symptoms of influenza-like illness (ILI) and how this may be impacted by enrolment in a placebo-controlled trial testing the feasibility of administering a Lactobacillus rhamnosus GG probiotic to prevent respiratory infection (2014-2017). Methods: The microbiome of the nasal (mid-turbinate) of 150 residents of long-term care homes was interrogated using 16S rRNA gene sequencing. Results: We identified a diverse and individualised microbiota which could be separated into nine distinct clusters based on Bray-Curtis distances. Samples collected during symptoms of ILI differed statistically from those collected pre- and post-cold and influenza season, and we observed decreased temporal stability (as measured by movement between clusters) in individuals who experienced ILI compared to those who did not. Conclusions: The use of probiotics decreased ILI-induced changes to the microbiota; however, it is not clear whether this decrease is sufficient to prevent respiratory illness.

Gene-gene relationships in an Escherichia coli accessory genome are linked to function and mobility.

The pangenome contains all genes encoded by a species, with the core genome present in all strains and the accessory genome in only a subset. Coincident gene relationships are expected within the accessory genome, where the presence or absence of one gene is influenced by the presence or absence of another. Here, we analysed the accessory genome of an Escherichia coli pangenome consisting of 400 genomes from 20 sequence types to identify genes that display significant co-occurrence or avoidance patterns with one another. We present a complex network of genes that are either found together or that avoid one another more often than would be expected by chance, and show that these relationships vary by lineage. We demonstrate that genes co-occur by function, and that several highly connected gene relationships are linked to mobile genetic elements. We find that genes are more likely to co-occur with, rather than avoid, another gene in the accessory genome. This work furthers our understanding of the dynamic nature of prokaryote pangenomes and implicates both function and mobility as drivers of gene relationships.

Model Systems to Study the Chronic, Polymicrobial Infections in Cystic Fibrosis: Current Approaches and Exploring Future Directions.

A recent workshop titled "Developing Models to Study Polymicrobial Infections," sponsored by the Dartmouth Cystic Fibrosis Center (DartCF), explored the development of new models to study the polymicrobial infections associated with the airways of persons with cystic fibrosis (CF). The workshop gathered 35+ investigators over two virtual sessions. Here, we present the findings of this workshop, summarize some of the challenges involved with developing such models, and suggest three frameworks to tackle this complex problem. The frameworks proposed here, we believe, could be generally useful in developing new model systems for other infectious diseases. Developing and validating new approaches to study the complex polymicrobial communities in the CF airway could open windows to new therapeutics to treat these recalcitrant infections, as well as uncovering organizing principles applicable to chronic polymicrobial infections more generally.

Evidence for Selection in the Abundant Accessory Gene Content of a Prokaryote Pangenome.

A pangenome is the complete set of genes (core and accessory) present in a phylogenetic clade. We hypothesize that a pangenome's accessory gene content is structured and maintained by selection. To test this hypothesis, we interrogated the genomes of 40 Pseudomonas species for statistically significant coincident (i.e., co-occurring/avoiding) gene patterns. We found that 86.7% of common accessory genes are involved in ≥1 coincident relationship. Further, genes that co-occur and/or avoid each other-but are not vertically inherited-are more likely to share functional categories, are more likely to be simultaneously transcribed, and are more likely to produce interacting proteins, than would be expected by chance. These results are not due to coincident genes being adjacent to one another on the chromosome. Together, these findings suggest that the accessory genome is structured into sets of genes that function together within a given strain. Given the similarity of the Pseudomonas pangenome with open pangenomes of other prokaryotic species, we speculate that these results are generalizable.

Horizontal Gene Transfer as a Source of Conflict and Cooperation in Prokaryotes.

Horizontal gene transfer (HGT) is one of the most important processes in prokaryote evolution. The sharing of DNA can spread neutral or beneficial genes, as well as genetic parasites across populations and communities, creating a large proportion of the variability acted on by natural selection. Here, we highlight the role of HGT in enhancing the opportunities for conflict and cooperation within and between prokaryote genomes. We discuss how horizontally acquired genes can cooperate or conflict both with each other and with a recipient genome, resulting in signature patterns of gene co-occurrence, avoidance, and dependence. We then describe how interactions involving horizontally transferred genes may influence cooperation and conflict at higher levels (populations, communities, and symbioses). Finally, we consider the benefits and drawbacks of HGT for prokaryotes and its fundamental role in understanding conflict and cooperation from the gene-gene to the microbiome level.

Culture-enriched metagenomic sequencing enables in-depth profiling of the cystic fibrosis lung microbiota.

Amplicon sequencing (for example, of the 16S rRNA gene) identifies the presence and relative abundance of microbial community members. However, metagenomic sequencing is needed to identify the genetic content and functional potential of a community. Metagenomics is challenging in samples dominated by host DNA, such as those from the skin, tissue and respiratory tract. Here, we combine advances in amplicon and metagenomic sequencing with culture-enriched molecular profiling to study the human microbiota. Using the cystic fibrosis lung as an example, we cultured an average of 82.13% of the operational taxonomic units representing 99.3% of the relative abundance identified in direct sequencing of sputum samples; importantly, culture enrichment identified 63.3% more operational taxonomic units than direct sequencing. We developed the PLate Coverage Algorithm (PLCA) to determine a representative subset of culture plates on which to conduct culture-enriched metagenomics, resulting in the recovery of greater taxonomic diversity-including of low-abundance taxa-with better metagenome-assembled genomes, longer contigs and better functional annotations when compared to culture-independent methods. The PLCA is also applied as a proof of principle to a previously published gut microbiota dataset. Culture-enriched molecular profiling can be used to better understand the role of the human microbiota in health and disease.

Culture and Molecular Profiling of the Respiratory Tract Microbiota.

Microbiome research of host-associated communities has been advanced recently through improvements in sequencing technologies and bioinformatic methods. Traditional microbiological culture, when combined with molecular techniques, can provide a sensitive platform to comprehensively study the airway microbiota. Here we describe the culture methods necessary to capture a large proportion of the airway microbiota and molecular methods for profiling bacterial communities through the 16S rRNA gene, which, when combined, offer a more complete picture of the diversity of airway microbial communities than either method alone.

Streptococcus pneumoniae Colonization Is Required To Alter the Nasal Microbiota in Cigarette Smoke-Exposed Mice.

Smokers have nasal microbiota dysbiosis, with an increased frequency of colonizing bacterial pathogens. It is possible that cigarette smoke increases pathogen acquisition by perturbing the microbiota and decreasing colonization resistance. However, it is difficult to disentangle microbiota dysbiosis due to cigarette smoke exposure from microbiota changes caused by increased pathogen acquisition in human smokers. Using an experimental mouse model, we investigated the impact of cigarette smoke on the nasal microbiota in the absence and presence of nasal pneumococcal colonization. We observed that cigarette smoke exposure alone did not alter the nasal microbiota composition. The microbiota composition was also unchanged at 12 h following low-dose nasal pneumococcal inoculation, suggesting that the ability of the microbiota to resist initial nasal pneumococcal acquisition was not impaired in smoke-exposed mice. However, nasal microbiota dysbiosis occurred as a consequence of established high-dose nasal pneumococcal colonization at day 3 in smoke-exposed mice. Similar to clinical reports on human smokers, an enrichment of potentially pathogenic bacterial genera such as Fusobacterium, Gemella, and Neisseria was observed. Our findings suggest that cigarette smoke exposure predisposes to pneumococcal colonization independent of changes to the nasal microbiota and that microbiota dysbiosis observed in smokers may occur as a consequence of established pathogen colonization.

A comprehensive evaluation of the sl1p pipeline for 16S rRNA gene sequencing analysis.

BACKGROUND: Advances in next-generation sequencing technologies have allowed for detailed, molecular-based studies of microbial communities such as the human gut, soil, and ocean waters. Sequencing of the 16S rRNA gene, specific to prokaryotes, using universal PCR primers has become a common approach to studying the composition of these microbiota. However, the bioinformatic processing of the resulting millions of DNA sequences can be challenging, and a standardized protocol would aid in reproducible analyses. METHODS: The short-read library 16S rRNA gene sequencing pipeline (sl1p, pronounced "slip") was designed with the purpose of mitigating this lack of reproducibility by combining pre-existing tools into a computational pipeline. This pipeline automates the processing of raw 16S rRNA gene sequencing data to create human-readable tables, graphs, and figures to make the collected data more readily accessible. RESULTS: Data generated from mock communities were compared using eight OTU clustering algorithms, two taxon assignment approaches, and three 16S rRNA gene reference databases. While all of these algorithms and options are available to sl1p users, through testing with human-associated mock communities, AbundantOTU+, the RDP Classifier, and the Greengenes 2011 reference database were chosen as sl1p's defaults based on their ability to best represent the known input communities. CONCLUSIONS: sl1p promotes reproducible research by providing a comprehensive log file, and reduces the computational knowledge needed by the user to process next-generation sequencing data. sl1p is freely available at https://bitbucket.org/fwhelan/sl1p .

The Evolving Cystic Fibrosis Microbiome: A Comparative Cohort Study Spanning 16 Years.

RATIONALE: The cystic fibrosis (CF) airways are infected with a diverse polymicrobial community. OBJECTIVES: Understanding how changes in the CF microbiome have occurred over time, similar to the observed changes in the prevalence of cultured pathogens, is key in understanding the microbiome's role in disease. METHODS: Drawing from a prospectively collected and maintained sputum biobank, we identified 45 patients with sputum samples collected between the ages of 18 and 21 years in three successive cohorts of adults transitioning to our CF clinic: A (1997-2000), B (2004-2007), and C (2010-2013). Patient demographics, clinical status, and medications were collected from detailed chart review. Microbial communities were assessed by Ilumina MiSeq sequencing of the variable 3 (V3) region of the 16S rDNA. RESULTS: The three cohorts were similar with respect to baseline demographics. There was a trend toward improved health and use of disease-modifying therapies in each successive cohort. Shannon diversity increased in the most recent cohort, suggesting an increase in the diversity of organisms between cohorts. Furthermore, the proportion of samples with Pseudomonas-dominated communities decreased over time, whereas Streptococcus increased. Although ß-diversity was associated with transition cohort, the greatest predictor of diversity remained lung function. Furthermore, core microbiome constituents were preserved across cohorts. CONCLUSIONS: Modest changes in the composition and structure of the microbiome of three successive cohorts of young adults with CF were observed, occurring in parallel with successive improvements in clinical status. Importantly, however, the core microbiome constituents were preserved across cohorts.

The effects of inhaled aztreonam on the cystic fibrosis lung microbiome.

BACKGROUND: Aztreonam lysine for inhalation (AZLI) is an inhaled antibiotic used to treat chronic Pseudomonas aeruginosa infection in CF. AZLI improves lung function and quality of life, and reduces exacerbations-improvements attributed to its antipseudomonal activity. Given the extremely high aztreonam concentrations achieved in the lower airways by nebulization, we speculate this may extend its spectrum of activity to other organisms. As such, we sought to determine if AZLI affects the CF lung microbiome and whether community constituents can be used to predict treatment responsiveness. METHODS: Patients were included if they had chronic P. aeruginosa infection and repeated sputum samples collected before and after AZLI. Sputum DNA was extracted, and the V3-hypervariable region of the 16S ribosomal RNA (rRNA) gene amplified and sequenced. RESULTS: Twenty-four patients naïve to AZLI contributed 162 samples. The cohort had a median age of 37.1 years, and a  median FEV1 of 44% predicted. Fourteen patients were a priori defined as responders for achieving ≥3% FEV1 improvement following initiation. No significant changes in alpha diversity were noted following AZLI. Furthermore, beta diversity demonstrated clustering with respect to patients, but had no association with AZLI use. However, we did observe a decline in the relative abundance of several individual operational taxonomic units (OTUs) following AZLI initiation suggesting that specific sub-populations of organisms may be impacted. Patients with higher abundance of Staphylococcus and anaerobic organisms including Prevotella and Fusobacterium were less likely to respond to therapy. CONCLUSIONS: Results from our study suggest potential alternate/additional mechanisms by which AZLI functions. Moreover, our study suggests that the CF microbiota may be used as a biomarker to predict patient responsiveness to therapy suggesting the microbiome may be harnessed for the personalization of therapies.

Longitudinal sampling of the lung microbiota in individuals with cystic fibrosis.

Cystic fibrosis (CF) manifests in the lungs resulting in chronic microbial infection. Most morbidity and mortality in CF is due to cycles of pulmonary exacerbations-episodes of acute inflammation in response to the lung microbiome-which are difficult to prevent and treat because their cause is not well understood. We hypothesized that longitudinal analyses of the bacterial component of the CF lung microbiome may elucidate causative agents within this community for pulmonary exacerbations. In this study, 6 participants were sampled thrice-weekly for up to one year. During sampling, sputum, and data (antibiotic usage, spirometry, and symptom scores) were collected. Time points were categorized based on relation to exacerbation as Stable, Intermediate, and Treatment. Retrospectively, a subset of were interrogated via 16S rRNA gene sequencing. When samples were examined categorically, a significant difference between the lung microbiota in Stable, Intermediate, and Treatment samples was observed in a subset of participants. However, when samples were examined longitudinally, no correlations between microbial composition and collected data (antibiotic usage, spirometry, and symptom scores) were observed upon exacerbation onset. In this study, we identified no universal indicator within the lung microbiome of exacerbation onset but instead showed that changes to the CF lung microbiome occur outside of acute pulmonary episodes and are patient-specific.

Reemergence of Lower-Airway Microbiota in Lung Transplant Patients with Cystic Fibrosis.

RATIONALE: Chronic lung infections are a hallmark of cystic fibrosis; they are responsible for progressive airway destruction and ultimately lead to respiratory death or the requirement for life-saving bilateral lung transplant. Furthermore, recurrent isolation of airway pathogens such as Pseudomonas aeruginosa in the allograft after transplant is associated with adverse outcomes, including bronchiolitis obliterans syndrome and acute infections. Little information exists on the impact of bilateral lung transplant on the lower-airway microbiota. OBJECTIVES: To compare, at a microbiome and single-pathogen level (P. aeruginosa), the bacterial communities in pre- and post-transplant samples. METHODS: We retrospectively accessed our biobank of sputum samples and sputum-derived bacterial pathogens for patients who had matched samples, including those who were clinically stable before transplant, those who had a pulmonary exacerbation before transplant, and those who had pulmonary exacerbation after transplant. We used 16S ribosomal RNA gene sequencing to characterize the lower-airway microbiome of 14 adult transplant patients with cystic fibrosis. Genotyping and phenotyping of P. aeruginosa isolates from 12 of these patients with matched isolates was performed. MEASUREMENTS AND MAIN RESULTS: Although α-diversity (richness and evenness) of patient microbiomes was similar before and after transplant, ß- diversity (core microbiome composition) measures stratified patients evenly into two groups with more similar and more dissimilar communities. P. aeruginosa strains isolated before transplant were found to reemerge in 11 of 12 patients; however, phenotypic variation was observed. CONCLUSIONS: These findings indicate that recolonization by P. aeruginosa after transplant is almost always strain specific, suggesting a within-host source. The polymicrobial colonization of the airways after transplant does not always reflect the pretransplant sputum microbiota.

Capturing the diversity of the human gut microbiota through culture-enriched molecular profiling.

BACKGROUND: The human gut microbiota has been implicated in most aspects of health and disease; however, most of the bacteria in this community are considered unculturable, so studies have relied on molecular-based methods. These methods generally do not permit the isolation of organisms, which is required to fully explore the functional roles of bacteria for definitive association with host phenotypes. Using a combination of culture and 16S rRNA gene sequencing, referred to as culture-enriched molecular profiling, we show that the majority of the bacteria identified by 16S sequencing of the human gut microbiota can be cultured. METHODS: Five fresh, anaerobic fecal samples were cultured using 33 media and incubation of plates anaerobically and aerobically resulted in 66 culture conditions for culture-enriched molecular profiling. The cultivable portion of the fecal microbiota was determined by comparing the operational taxonomic units (OTUs) recovered by 16S sequencing of the culture plates to OTUs from culture-independent sequencing of the fecal sample. Targeted isolation of Lachnospiraceae strains using conditions defined by culture-enriched molecular profiling was carried out on two fresh stool samples. RESULTS: We show that culture-enriched molecular profiling, utilizing 66 culture conditions combined with 16S rRNA gene sequencing, allowed for the culturing of an average of 95 % of the OTUs present at greater than 0.1 % abundance in fecal samples. Uncultured OTUs were low abundance in stool. Importantly, comparing culture-enrichment to culture-independent sequencing revealed that the majority of OTUs were detected only by culture, highlighting the advantage of culture for studying the diversity of the gut microbiota. Applying culture-enriched molecular profiling to target Lachnospiraceae strains resulted in the recovery of 79 isolates, 12 of which are on the Human Microbiome Project's "Most Wanted" list. CONCLUSIONS: We show that, through culture-enriched molecular profiling, the majority of the bacteria in the human gut microbiota can be cultured and this method revealed greater bacterial diversity compared to culture-independent sequencing. Additionally, this method could be applied for the targeted recovery of a specific bacterial group. This approach allows for the isolation of bacteria of interest from the gut microbiota, providing new opportunities to explore mechanisms of microbiota-host interactions and the diversity of the human microbiota.

Partitioning and correlating subgroup characteristics from Aligned Pattern Clusters.

MOTIVATION: Evolutionarily conserved amino acids within proteins characterize functional or structural regions. Conversely, less conserved amino acids within these regions are generally areas of evolutionary divergence. A priori knowledge of biological function and species can help interpret the amino acid differences between sequences. However, this information is often erroneous or unavailable, hampering discovery with supervised algorithms. Also, most of the current unsupervised methods depend on full sequence similarity, which become inaccurate when proteins diverge (e.g. inversions, deletions, insertions). Due to these and other shortcomings, we developed a novel unsupervised algorithm which discovers highly conserved regions and uses two types of information measures: (i) data measures computed from input sequences; and (ii) class measures computed using a priori class groupings in order to reveal subgroups (i.e. classes) or functional characteristics. RESULTS: Using known and putative sequences of two proteins belonging to a relatively uncharacterized protein family we were able to group evolutionarily related sequences and identify conserved regions, which are strong homologous association patterns called Aligned Pattern Clusters, within individual proteins and across the members of this family. An initial synthetic demonstration and in silico results reveal that (i) the data measures are unbiased and (ii) our class measures can accurately rank the quality of the evolutionarily relevant groupings. Furthermore, combining our data and class measures allowed us to interpret the results by inferring regions of biological importance within the binding domain of these proteins. Compared to popular supervised methods, our algorithm has a superior runtime and comparable accuracy. AVAILABILITY AND IMPLEMENTATION: The dataset and results are available at www.pami.uwaterloo.ca/∼ealee/files/classification2015 CONTACT: akcwong@uwaterloo.ca SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Streptococcus pneumoniae Colonization Disrupts the Microbial Community within the Upper Respiratory Tract of Aging Mice.

Nasopharyngeal colonization by the Gram-positive bacterium Streptococcus pneumonia is a prerequisite for pneumonia and invasive pneumococcal diseases. Colonization is asymptomatic, involving dynamic and complex interplay between commensals, the host immune system, and environmental factors. The elderly are at an increased risk of developing pneumonia, which might be due to changes in the respiratory microbiota that would impact bacterial colonization and persistence within this niche. We hypothesized that the composition of the upper respiratory tract (URT) microbiota changes with age and subsequently can contribute to sustained colonization and inefficient clearance of S. pneumoniae To test this, we used a mouse model of pneumococcal colonization to compare the composition of the URT microbiota in young, middle-aged, and old mice in the naive state and during the course of colonization using nasal pharyngeal washes. Sequencing of variable region 3 (V3) of the 16S rRNA gene was used to identify changes occurring with age and throughout the course of S. pneumonia colonization. We discovered that age affects the composition of the URT microbiota and that colonization with S. pneumoniae is more disruptive of preexisting communities in older mice. We have further shown that host-pathogen interactions followingS. pneumonia colonization can impact the populations of resident microbes, including Staphylococcus and Haemophilus. Together, our findings indicate alterations to the URT microbiota could be detrimental to the elderly, resulting in increased colonization of S. pneumonia and decreased efficiency in its clearance.

Clinical Insights into Pulmonary Exacerbations in Cystic Fibrosis from the Microbiome. What Are We Missing?

Pulmonary exacerbations account for much of the decrease in lung function and consequently most of the morbidity and mortality in patients with cystic fibrosis. These events are driven by an acute inflammatory response to infection. Recent technological advancements in molecular profiling techniques have allowed for a proliferation of microbiome studies of the lower airways of patients with cystic fibrosis. But these methods may not provide a comprehensive and unbiased measure of the lung microbiota in these patients and molecular profiles do not always translate to quantitative microbiology. Furthermore, these studies have not yet been able to provide much in the way of mechanistic insights into exacerbations or to guide patient therapy. We propose a model in which pulmonary exacerbations may be driven by an active subpopulation of the lung microbiota, which may represent only a small portion of the microbiota measured in a clinical sample. Methodology should be focused on the ultimate goal, which is to use the best available approaches to provide accurate quantitative measures of the microbiome to inform clinical decisions and provide rapid assessment of treatment efficacy. These strategies would be relevant to other chronic lung diseases such as chronic obstructive pulmonary disease and neutrophilic asthma.

Pregnancy-related changes in the maternal gut microbiota are dependent upon the mother's periconceptional diet.

Shifts in the maternal gut microbiome have been implicated in metabolic adaptations to pregnancy. We investigated how pregnancy and diet interact to influence the composition of the maternal gut microbiota. Female C57BL/6 mice were fed either a control or a high fat diet for 8 weeks prior to mating. After confirmation of pregnancy, maternal weight gain and food intake were recorded. Fecal pellets were collected at 2 timepoints prior to mating (at the beginning of the experiment, and after 6 weeks of the specified diet) and at 4 timepoints during pregnancy (gestation day 0.5, 5.5, 10.5, and 15.5). The microbial composition and predicted metabolic functionality of the non-pregnant and pregnant gut was determined via sequencing of the variable 3 region of the 16S rRNA gene. Upon conception, differences in gut microbial communities were observed in both control and high fat-fed mice, including an increase in mucin-degrading bacteria. Control versus high fat-fed pregnant mice possessed the most profound changes to their maternal gut microbiota as indicated by statistically significant taxonomic differences. High fat-fed pregnant mice, when compared to control-fed animals, were found to be significantly enriched in microbes involved in metabolic pathways favoring fatty acid, ketone, vitamin, and bile synthesis. We show that pregnancy-induced changes in the female gut microbiota occur immediately at the onset of pregnancy, are vulnerable to modulation by diet, but are not dependent upon increases in maternal weight gain during pregnancy. High fat diet intake before and during pregnancy results in distinctive shifts in the pregnant gut microbiota in a gestational-age dependent manner and these shifts predict significant differences in the abundance of genes that favor lipid metabolism, glycolysis and gluconeogenic metabolic pathways over the course of pregnancy.

The Evolution of the Scavenger Receptor Cysteine-Rich Domain of the Class A Scavenger Receptors.

The class A scavenger receptor (cA-SR) family is a group of five evolutionarily related innate immune receptors. The cA-SRs are known for their promiscuous ligand binding; as they have been shown to bind bacteria, such as Streptococcus pneumoniae and Escherichia coli, as well as different modified forms of low-density lipoprotein. Three of the five family members possess a scavenger receptor cysteine-rich (SRCR) domain while the remaining two receptors lack the domain. Previous work has suggested that the macrophage-associated receptor with collagenous structure (MARCO) shares a recent common ancestor with the non-SRCR-containing receptors; however, the origin of the SRCR domain within the cA-SRs remains unknown. We hypothesize that the SRCR domains of the cA-SRs have a common origin that predates teleost fish. Using the newly available sequence data from sea lamprey and ghost shark genome projects, we have shown that MARCO shares a common ancestor with the SRCR-containing proteins. In addition, we explored the evolutionary relationships within the SRCR domain by reconstructing the ancestral SRCR domains of the cA-SRs. We identified a motif that is highly conserved between the cA-SR SRCR domains and the ancestral SRCR domain that consist of WGTVCDD. We also show that the GRAEVYY motif, a functionally important motif within MARCO, is poorly conserved in the other cA-SRs and in the reconstructed ancestral domain. Further, we identified three sites within MARCO's SRCR domain, which are under positive selection. Two of these sites lie adjacent to the conserved WGTVCDD motif, and may indicate a potential biological function for these sites. Together, these findings indicate a common origin of the SRCR domain within the cA-SRs; however, different selective pressures between the proteins may have caused MARCOs SRCR domain to evolve to contain different functional motifs when compared to the other SRCR-containing cA-SRs.