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Faecalibacterium prausnitzii (F. prausnitzii) is a gram-positive, non-spore-forming anaerobic bacterium belonging to the Firmicutes phylum. It is one of the most abundant members of the healthy human gut microbiota, constituting over 5% of the total bacterial population in healthy adults. This anaerobic bacterium has gained recognition as a crucial contributor to intestinal health and a potential biosensor for various gut-related conditions.

(10.1016/j.micpath.2020.104344.; 10.1093/femsre/fuad039)

GENES

BCoAT in F. prausnitzii is central to butyrate production, underpinning the bacterium’s crucial role in gut health. Its activity not only supports anti-inflammatory mechanisms but also highlights its therapeutic potential for managing conditions like inflammatory bowel disease and rheumatoid arthritis. Further research into the regulation of BCoAT may unlock new opportunities for microbiota-based therapies.

The PTS system, encoded by the ptsP gene, is central to carbohydrate metabolism in Faecalibacterium prausnitzii, facilitating energy production and butyrate synthesis. This pathway underscores the bacterium’s vital role in gut health, as butyrate supports anti-inflammatory processes and serves as an energy source for intestinal cells. Investigating the regulation of the ptsP gene and the PTS system could reveal new strategies for microbiota-based therapies to enhance intestinal health and treat related disorders.

MutS domain I is a essential protein in bacterial DNA maintenance, particularly in DNA mismatch repair and methylation systems. This dual-function protein plays a crucial role in maintaining DNA integrity through its repair and modification capabilities in Faecalibacterium prausnitzii, a significant member of the human gut microbiome representing about 3.8% of colonic microbiota in healthy adults.

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Code from GitHub where the information was taken from

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The GenBank record, NZ_DS483503.1, corresponds to a segment of the Faecalibacterium prausnitzii M21/2 genome, specifically from nucleotide positions 313,586 to 314,932 from the original strand.

This region encompasses a gene encoding a protein of 448 amino acids.

There are 3 features: Source, Gene and CDS.

Source:

Location: 0 : 1347

Organism: Faecalibacterium prausnitzii M21/2

Host: Homo sapiens

Gene:

Locus (ID) : FAEPRAM212_RS11550 (75069048)

CDS:

Protein: WP_044960620.1

Function: Catalysis of the transfer of a coenzyme A (CoA) group from one compound (donor) to another (acceptor).

Translated Sequence

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NetPhosBac analysis predicts potential phosphorylation sites across the WP_044960620.1 sequence.

Serine Phosphorylation Sites --> these residues show significant phosphorylation potentia. This suggests an important role for serine phosphorylation in the protein's functionality and regulation.

Threonine Phosphorylation Sites -->these sites appear less frequent compared to serine. This indicates a secondary layer of regulatory potential, likely contributing to structural flexibility or modulating specific protein-protein interactions.

Distribution of Phosphorylation Sites -->distributed throughout the sequence, with specific regions showing notable clustering. These clustered regions likely correspond to functional domains, where phosphorylation could play a critical role.

The phosphorylation profile of WP_044960620.1 suggests it is a dynamically regulated protein. These phosphorylation events likely play a critical role in modulating its activity, structural configuration, or interactions in cellular pathways, possibly contributing to functions like metabolic regulation, signaling, or environmental adaptability.

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The investigation yielded no conclusive data regarding the gene variants under study or their associated biological effects. No significant findings emerged from the analysis comparing different genetic variations and their potential impacts on biological processes or outcomes.

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Phylogenetic Analysis of the butyrylCoA Protein

UPGMA Tree

1. General Structure and Clustering:

The UPGMA tree reveals a hierarchical clustering of species, assuming a constant molecular clock.

The query sequence is positioned close to Roseburia hominis A2-183 and Anaerostipes caccae L1-92, suggesting a shared evolutionary history and high functional similarity.

Fasciola hepatica is more distantly related, forming a separate clade with Clostridium kluyveri DSM 555, indicating a lower degree of similarity to the query sequence.

2. Branch Length Interpretation:

The branch length between the query sequence and its closest neighbors (Roseburia and Anaerostipes) is relatively short, reflecting high conservation.

The longer branches connecting Fasciola hepatica and Clostridium kluyveri indicate a greater evolutionary divergence from the query sequence.

3. Functional Insights:

The close grouping of Roseburia and Anaerostipes, both known for their roles in butyrate metabolism, underscores the potential functional importance of the query sequence in similar pathways.

NJ Tree

1. General Structure and Clustering:

The NJ tree, which does not assume a molecular clock, presents a slightly different evolutionary relationship.

The query sequence still clusters closely with Roseburia hominis A2-183 and Anaerostipes caccae L1-92, confirming their evolutionary proximity and functional similarity.

Fasciola hepatica and Clostridium kluyveri DSM 555 again form a separate group, with clear divergence from the core bacterial clade.

2. Branch Length Comparison:

Branch lengths in the NJ tree are slightly more variable, reflecting different rates of evolution among taxa.

The separation between Fasciola hepatica and the bacterial clades is even more pronounced here, emphasizing its evolutionary distance from butyrate-metabolizing species.

3. Functional Insights:

Similar to the UPGMA tree, the proximity of the query sequence to Roseburia and Anaerostipes reinforces its likely role in butyrate metabolism.

The placement of Fasciola hepatica and Clostridium kluyveri suggests distinct evolutionary pressures and metabolic roles compared to the query sequence.

Key Comparisons Between UPGMA and NJ Trees

1. Consistency in Clustering:

Both trees consistently place the query sequence near Roseburia and Anaerostipes, highlighting strong evolutionary and functional relationships.

2. Differences in Branch Lengths:

The NJ tree provides a more accurate depiction of evolutionary distances by accounting for variable rates of evolution, while the UPGMA tree simplifies relationships with its constant-rate assumption.

3. Implications of Clustering Patterns:

The stable clustering of the query sequence with butyrate-metabolizing bacteria across both methods strengthens the hypothesis of its involvement in similar metabolic pathways.

Conclusion

The phylogenetic trees derived from UPGMA and NJ methods consistently position the query sequence in close association with Roseburia hominis and Anaerostipes caccae, underscoring its likely role in butyrate metabolism. Differences in branch lengths between the two methods highlight the evolutionary divergence of Fasciola hepatica and Clostridium kluyveri, suggesting distinct evolutionary pressures.

The analysis of these dendrograms complements the BLAST results by visually confirming the query sequence’s close relationship with bacteria involved in carbohydrate fermentation and fatty acid metabolism.

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Name: Butyryl-CoA: acetate CoA-transferase

ID: 75069048

Location: 2 → 447

Type: Protein coding --> butyryl-CoA: acetate CoA-transferase (BCoAT)

Key enzyme in the metabolic processes of Faecalibacterium prausnitzii, particularly in its production of butyrate. This enzyme facilitates the final step of butyrate synthesis, converting butyryl-CoA and acetate into butyrate and acetyl-CoA (https://doi.org/10.1038/ismej.2016.176).

BCoAT operates within the reverse β-oxidation pathway, alongside enzymes such as acetyl-CoA acetyltransferase and butyryl-CoA dehydrogenase (https://doi.org/10.1038/s41598-023-51059-3).

BCoAT mediates the transfer of the CoA group from butyryl-CoA to acetate, producing butyrate and acetyl-CoA. This reaction is critical because it regenerates acetyl-CoA for continued metabolic cycling and contributes to energy production (https://doi.org/10.1038/ismej.2016.176).

The activity of BCoAT supports "acetate cross-feeding," enabling F. prausnitzii to utilize acetate during glucose metabolism, despite the bacterium’s inability to use acetate as a sole energy source (10.1093/ibd/izy182).

The butyrate produced by F. prausnitzii, mediated through BCoAT activity, offers several health advantages:

Energy supply for colonocytes

Anti-inflammatory effects

Potential protective roles against colorectal cancer and inflammatory bowel diseases.

(https://doi.org/10.1186/s13075-023-03118-3)

Acetate availability modulates the expression of genes in F. prausnitzii, potentially influencing BCoAT activity and butyrate production (https://doi.org/10.1038/s41598-023-51059-3).

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The EEU96797.1 protein (butyryl-CoA:acetate CoA-transferase) plays a significant role in the metabolism of short-chain fatty acids (SCFAs), particularly in the conversion of butyryl-CoA to butyrate.

AckA: Interaction with acetate kinase (ackA) suggests a connection to acetate metabolism, crucial for SCFA production and energy balance.

Pta: Links with phosphate acetyltransferase (pta) highlight involvement in acetyl-CoA metabolism, reinforcing the protein's central role in fatty acid pathways.

LeuA: Suggests potential overlap with amino acid biosynthesis pathways, such as leucine metabolism.

NifJ: Indicates a potential role in electron transport or redox balance, possibly tied to energy production in anaerobic conditions.

Crt: Points to carotenoid biosynthesis pathways, which may relate to oxidative stress response or membrane dynamics.

SCFA Production: The primary role of EEU96797.1 lies in butyrate synthesis, which supports gut health and microbial ecology.

Energy Metabolism: The interactions with metabolic enzymes like ackA and pta emphasize its role in coupling butyrate production with cellular energy demands.

Environmental Adaptation: Its links to redox-active proteins (e.g., NifJ) and carotenoid-related pathways (e.g., Crt) suggest it contributes to bacterial survival and functionality under varying environmental conditions.

EEU96797.1 is a central player in SCFA metabolism, particularly in butyrate production, with broader implications for energy regulation and adaptation in anaerobic environments. Its interactions underline its metabolic versatility and significance in bacterial communities, such as those in the human gut( (PMID: 23821742)).

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EEU96797.1 protein (Faecalibacterium prausnitzii A2165) - STRING interaction network

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Name: ptsP

ID: 75068783

Location: 6 → 540

Type: Protein coding --> phosphoenolpyruvate--protein phosphotransferase

Essential enzyme in bacterial metabolism, particularly in the phosphoenolpyruvate-dependent sugar phosphotransferase system (PTS). This system is a critical metabolic pathway for the uptake and phosphorylation of sugars in bacteria (https://doi.org/10.1111/1462-2920.15681).

The PTS system regulates sugar uptake, ensuring the efficient utilization of carbon sources. It is also involved in signal transduction, integrating metabolic signals and environmental conditions to optimize bacterial growth and energy efficiency (https://doi.org/10.1016/j.mib.2013.06.003).

Faecalibacterium prausnitzii utilizes carbohydrates available in the intestinal environment, such as oligosaccharides, monosaccharides, and fermentable polysaccharides, to generate energy and produce butyrate—a metabolite crucial for intestinal epithelial health. The PTS system facilitates the efficient uptake of sugars, such as glucose or fructose, by phosphorylating them during transport into the cell (https://doi.org/10.1111/1462-2920.15681).

Carbohydrate metabolism in F. prausnitzii, initiated by the action of the PTS system, contributes to the formation of metabolic intermediates that fuel the butyrate synthesis pathway. Butyrate is well-known for its anti-inflammatory properties and its role as an energy source for colonocytes (intestinal cells) (10.1128/MMBR.00001-14).

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With InterPro we can see that are two main families in our protein: Butyryl-CoA:acetate CoA-transferase (represents one mechanism for reclaiming CoA from butyryl-CoA at the end of butyrate biosynthesis, namely transfer of CoA to acetate) and Acetyl-CoA hydrolase-related (includes enzymes involved in acetyl-CoA related pathways).

Acetyl-CoA hydrolase/transferase, C-terminal domain --> take part in pathways involving acetyl-CoA, including acetyl-CoA hydrolase, succinyl-CoA.

Acetyl-CoA hydrolase/transferase, N-terminal --> engage in processes that involve acetyl-CoA, such as the actions of acetyl-CoA hydrolase, propionyl-CoA:succinate CoA transferase, and succinyl-CoA. Acetyl-CoA hydrolase facilitates the conversion of acetyl-CoA into acetate.

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InterPro provides functional analysis of proteins by classifying them into families and predicting domains and important sites. We combine protein signatures from a number of member databases into a single searchable resource, capitalising on their individual strengths to produce a powerful integrated database and diagnostic tool.

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The MEME (Multiple EM for Motif Elicitation) analysis of the BCoAT and its 5 homologue sequences has revealed three highly significant motifs across the protein sequences.

(This analysis was constrained to identify the three most conserved amino acid sequences, which aligns with the imposed limit of 3 motifs.)

Motifs 1, 2, and 3 are present in all sequences with extremely small E-values, indicating strong statistical support for their conservation and potential biological significance.

Motif 1 emerges as the strongest motif, with consistently small E-values (e.g., 6.22e-54 in G2SYC0(Roseburia hominis A2-183), 4.66e-45 in C6EUD4 (Fasciola hepatica)).

Motif 3 while slightly variable in E-value (e.g., 1.11e-39 in P38942 (Clostridium kluyveri DSM 555)vs. 5.46e-51 in Q0AVM5(Syntrophomonas wolfei subsp. wolfei str. Goettingen G311)), remains highly significant across all sequences.

The differences in where the motifs are located in each sequence suggest some flexibility, but their consistent presence and spacing could mean they have important roles, like enzyme active sites or binding regions.

The conserved motifs are likely to play crucial roles in shared evolutionary and biological functions, such as enzymatic activity, structural integrity, or regulatory interactions.

In conclusion, the MEME results reveal that motifs 1, 2, and 3 are highly conserved, functionally important elements across the analyzed sequences. These findings suggest strong evolutionary pressures to maintain these motifs due to their biological relevance.

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NetPhosBac analysis predicts potential phosphorylation sites across the WP_005925321.1 sequence.

Serine Phosphorylation Sites --> numerous serine residues have high phosphorylation potential, suggesting a key regulatory role in the protein's function through serine phosphorylation.

Threonine Phosphorylation Sites -->also show notable phosphorylation potential, though they are less frequent compared to serine. This indicates that threonine phosphorylation could contribute additional layers of regulation, possibly affecting structural stability or protein interactions.

Distribution of Phosphorylation Sites -->distributed throughout the sequence, with certain regions displaying higher clustering of phosphorylation potential. These regions may correspond to functional domains or motifs that rely on phosphorylation for activation, interaction, or modulation of activity.

The phosphorylation profile of WP_005925321.1 suggests it is a dynamically regulated protein, likely involved in critical cellular processes. Phosphorylation events may influence its role in signaling, structural flexibility, or cellular adaptation mechanisms, marking it as a protein with diverse functional capabilities.

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Code from GitHub where the information was taken from

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The GenBank record, NZ_DS483503 , corresponds to a segment of the Faecalibacterium prausnitzii M21/2 genome, specifically from nucleotide positions 23763 to 25406.

This region encompasses a gene encoding a protein of 547 amino acids.

There are 3 main features: Source, Gene and CDS.

Source:

Location: 0 : 1644

Organism: Faecalibacterium prausnitzii M21/2

Host: Homo sapiens

Gene:

Gene (ID): ptsP (75068783)

CDS:

Protein: WP_005925321.1

Function: Catalysis of the reaction: phosphoenolpyruvate + protein L-histidine = pyruvate + protein N(pi)-phospho-L-histidine

Translated Sequence

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Function and Characteristics:

The protein is 2701 amino acids long

Contains a MutS domain I region (approximately between amino acids 363-429)

Functions as an adenine-specific DNA methylase (N12 class)

Involved in replication, recombination, and DNA repair processes

Contains multiple functional domains including:

DNA methylase capabilities

ATP-binding motifs

DNA binding regions

Key Features:

Located in the outer membrane (based on Psort location score: 9.49)

Part of DNA mismatch repair system

Contains multiple protein motifs related to:

DNA methylation

ATP-dependent molecular functions

DNA binding and repair

The protein appears to play an important role in maintaining DNA integrity through its methylation and repair functions in F. prausnitzii, which is a significant bacterial species found in the human gut microbiome.

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STRING analysis showed that the PtsP protein is a key component of the bacterial Phosphotransferase System (PTS), which regulates metabolism and cellular signaling. It plays a critical role in metabolic adaptation and environmental response.

Pyk: Links PtsP to energy metabolism via pyruvate regulation.

PtbA: Suggests involvement in carboxylic acid metabolism and phosphate transfer.

PfkB: Indicates a role in glycolysis and central metabolic flux regulation.

EEU980631 and related hypothetical proteins: Highlight potential unknown functional pathways for further exploration.

PtsP integrates metabolic signals and environmental cues, coordinating essential functions like energy production and nutrient uptake(PMID: 17158705).

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The MEME (Multiple EM for Motif Elicitation) analysis of the BCoAT and its 45 homologue sequences has revealed three highly significant motifs across the protein sequences.

(This analysis was constrained to identify the three most conserved amino acid sequences, which aligns with the imposed limit of 3 motifs.)

Motif 1 identified as the most conserved motif across all sequences. Exhibits extremely small E-values (e.g., 5.22e-64 in O31149 (Listeria monocytogenes EGD-e), 2.84e-32 in P23536 (Cupriavidus necator H16)), providing strong statistical support for its conservation and potential functional importance.

Motif 2 displayed similarly high levels of conservation, (with a minimum E-value of 5.21e-50 in Q92D19 (Listeria innocua Clip11262). This motif covers sequences with minimal variability, indicating a shared functional role.

Motif 3 while slightly variable in its E-values ( 1.45e-29 in Q9ZAD8 (Lactococcus cremoris) as the minimum), this motif remains conserved across all sequences. Its presence is indicative of a conserved role, possibly related to structural stability or regulatory interactions.

The identified motifs likely play crucial roles in the proteins biological and evolutionary functions. Their high degree of conservation suggests significant functional importance.

The MEME analysis highlights that Motifs 1, 2, and 3 are conserved, functionally critical elements across the analyzed sequences. The strong evolutionary pressure to preserve these motifs underscores their biological significance, likely tied to shared functional roles across the dataset.

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Name: MutS Domain I Protein
ID: EDP20631.1
Location: 859977 → 868082 (ABED02000029.1)
Type: Protein coding → DNA Mismatch Repair / DNA Methylase

The MutS Domain I Protein is a vital enzyme in bacterial DNA maintenance, primarily functioning within the mismatch repair (MMR) system. This system is essential for identifying and repairing replication errors, preserving genomic stability, and minimizing mutation rates (https://doi.org/10.1016/j.bbrc.2007.06.056).

MutS detects mismatches by sensing structural distortions and altered base dynamics in DNA (https://doi.org/10.1016/j.jmb.2007.08.065). This specificity is critical for initiating repair mechanisms that prevent genomic instability.

MutS safeguards genomic stability, allowing Faecalibacterium prausnitzii to adapt within the intestinal environment. Maintaining stable DNA in F. prausnitzii is essential for its contribution to gut health, including intestinal homeostasis and anti-inflammatory processes (https://doi.org/10.1126/science.1110591).

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Based on the Phobius prediction results:

The analysis shows no transmembrane segments in the protein, suggesting it's unlikely to pass through the cell membrane. The protein has a high chance of being found in the non-cytoplasmic area, which means it's probably outside the cell or in organelles. There were no signal peptides detected. In summary, this protein is likely located outside the cell's cytoplasm, doesn't have any parts that cross the membrane, and lacks signal peptides for directing its movement.

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There was no information found in the matters of the gene variants and their biological impact.

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Phylogenetic Analysis of the PtsP Protein

UPGMA Tree Analysis

The UPGMA tree groups the query sequence in a distant branch, separating it from most bacterial clusters. The species closest to the query include archaeal species such as Archaeoglobus fulgidus DSM 4304 and Halofarex volcanii DS2, reflecting a more ancient evolutionary divergence.

Clear clustering is observed among bacterial groups. For instance:

Firmicutes Cluster: Includes Bacillus sp. and Geobacillus stearothermophilus, showing tight evolutionary proximity within their phylum.

Proteobacteria Cluster: Includes species like Escherichia coli and Salmonella enterica, which are closely related but distinct from the archaeal clade.

The constant-rate assumption of the UPGMA method reinforces the hierarchical branching, but it potentially oversimplifies evolutionary relationships for organisms with variable mutation rates.

NJ Tree Analysis

The NJ tree presents a similar topology but reveals more nuanced evolutionary distances:

The query sequence is again distantly located, with its nearest neighbors being archaeal species (Archaeoglobus fulgidus DSM 4304 and Halofarex volcanii DS2). These long branch lengths emphasize the evolutionary divergence between the query sequence and bacterial proteins.

A Firmicutes cluster is evident, with species like Bacillus sp. and Geobacillus stearothermophilus forming a tightly grouped clade.

Proteobacteria species (Escherichia coli and Salmonella enterica) show strong similarity but are clearly separated from the archaeal cluster and the query sequence.

Unlike the UPGMA tree, the NJ method accounts for variable evolutionary rates, providing a more accurate depiction of these relationships.

Key Observations

1. Distant Position of the Query: In both UPGMA and NJ trees, the query sequence is positioned far from bacterial species, indicating significant evolutionary divergence. Its proximity to archaeal species suggests a potential origin or functional adaptation in environments associated with archaea.

2. Consistency in Clustering: Firmicutes (Bacillus, Geobacillus) and Proteobacteria (E. coli, Salmonella) form stable clades across both trees, reflecting conserved evolutionary relationships within these bacterial phyla.

3. Divergence of Archaeal Lineages: Archaeal species are distinct outgroups in both methods, reinforcing their evolutionary separation from bacterial proteins.

Conclusion

The phylogenetic position of the query sequence highlights its evolutionary divergence, with closer affinity to archaeal species like Archaeoglobus fulgidus DSM 4304 and Halofarex volcanii DS2. This suggests the possibility of functional or environmental adaptation linked to archaea. Despite methodological differences between UPGMA and NJ trees, both consistently place the query far from bacterial clades, underscoring its distinct evolutionary trajectory.

Does this revised analysis now align with the trees in the image? Let me know if you'd like further adjustments!

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UniProt was used because it provides detailed information about the protein.

Subcellular location : none was found

Structure : analyzed with AlphaFold

Family : Acetyl-CoA hydrolase/transferase family, suggesting that the protein is involved in metabolic processes related to CoA, playing a role in the metabolism energy.

Domain : there are two annotated domains --> Acetyl-CoA hydrolase/transferase N-terminal domain ( Is associated with the enzymatic activity at the N-terminal, and likely, contributes to the catalytic transfer or hydrolysis of acetyl (positions 14-191)); --> Acetyl-CoA hydrolase/transferase C-terminal (May provide functional or structural stability and it may complement the enzymatic activity of the other domain (positions 288-445)).

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UniProt is the world’s leading high-quality, comprehensive and freely accessible resource of protein sequence and functional information.

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AlphaFold was used to get a detailed 3D model of the BCoAT protein. It´s possible to see that this protein is composed with alpha-helix and beta-sheets.

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InterPro was used to identify and classify the protein into families and domains based on structural and functional patterns.

PTS family is essential for the transportation of sugar in bacteria. The presence of this family may indicate that the protein is involved in the phosphorylation of sugars, enabling their uptake into the cell.

PEP-utilizers domains, crucial for the sugar transport function in the PTS family.

The other domains, such as the phosphohistidine domain, indicates potencial functions beyond sugar transport, possibly related with regulation.

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InterPro provides functional analysis of proteins by classifying them into families and predicting domains and important sites. We combine protein signatures from a number of member databases into a single searchable resource, capitalising on their individual strengths to produce a powerful integrated database and diagnostic tool.

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Phobius predicts if the protein is transmembrane and whether it contains signal peptides.

The high probability of amino acids being located in a non cytoplasmatic region (blue line) suggests that the protein is also in the non-cytoplasmatic space.

The presence of transmembrane domains (purple spikes) indicates that the protein is involved with specific interactions with other proteins, the protein may be secreted.

The protein is located in the cytoplasm (green line represents areas with probability of regions of the protein being located inside the cell).

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With UniProt we can analyze multiple information about the protein, such as:

Subcellular location: Cytoplasm

Structure: analyzed using AlphaFold

Family: the protein belongs to the family of enzymes that utilize phosphoenolpyruvate (PEP), suggesting that the protein is probably involved in metabolic processes that use PEP as a substrate or a cofactor.

Domain: there are three main domains in this protein --> N-terminal domain ( Associated with enzymes of the phosphotransferase system. Region likely involved in the transfer of phosphate groups);

PEP-utilizing domain (domain characteristic of enzymes that use PEP. Probably contains an active site where the PEP reaction occurs);

PEP-utilising enzyme C-terminal (Related to PEP. It may have additional functions or complement the PEP- utilizing domain)

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UniProt is the world’s leading high-quality, comprehensive and freely accessible resource of protein sequence and functional information.

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Detailed 3D model of the protein, possessing several alpha-helix and beta-sheets.

In the AlphaFold we can also get information about the biological function of the protein.

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InterPro analysis was used to classify protein EEU95773.1 into families and domains, leveraging structural and functional patterns.

DNA_Mismatch_Repair_MutS_N --> indicates a role in DNA repair, specifically in the mismatch repair (MMR) system.

P-loop_NTPase --> A highly conserved domain involved in ATP binding and hydrolysis, which is crucial for many molecular processes such as DNA repair, helicase activity, or regulatory functions.

Helicase_ATP_binding and Helicase_C Domains -->These domains are characteristic of helicase superfamilies, suggesting that EEU95773.1 may function in DNA or RNA unwinding, a key process in replication, transcription, or repair.

SAM-dependent_MTsases_sf --> The presence of a S-adenosylmethionine-dependent methyltransferase domain suggests potential roles in methylation reactions. These activities may relate to regulatory processes.

SNF2_N --> This domain suggests chromatin remodeling functions.

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InterPro provides functional analysis of proteins by classifying them into families and predicting domains and important sites. We combine protein signatures from a number of member databases into a single searchable resource, capitalising on their individual strengths to produce a powerful integrated database and diagnostic tool.

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Based on the Phobius prediction results:

The analysis show absence of transmembrane regions, suggests that the protein lacks membrane-spanning segments and is not embedded within the cell membrane. The consistently high probability of amino acids being located in a non-cytoplasmic region (blue line) indicates that the protein predominantly resides in extracellular or non-cytoplasmic spaces. There is no indication of signal peptides in the plot, suggesting the protein does not use conventional secretion pathways for extracellular transport.

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AlphaFold was used to get a detailed 3D model of the protein.

This protein is composed by beta-sheets and alpha-helix.

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Highest Abundance:

Alanine (A)

Glutamic Acid (E)

Leucine (L)

Lowest Abundance:

Cysteine (C)

Tryptophan (W)

Implications:

High proportion of charged residues (E) consistent with acidic pI (4.96)

Low tryptophan content explains low aromaticity index (0.08)

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Bioinformatics Laboratories project promotes the advanced use of bioinformatics tools to analyze a set of genes and sequences of interest from microorganisms in the human intestinal microbiome. - LB_project/results/figures/protein at protein_analysis · cgomes03/LB_project

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Phylogenetic Analysis of the MutS Protein

UPGMA Tree

General Structure and Clustering:

The UPGMA tree reveals hierarchical clustering based on a constant molecular clock assumption.

The query sequence groups closely with Paramecium bursaria Chlorella virus NC1A and Escherichia phage P1, suggesting a shared evolutionary trajectory.

Streptomyces albus G is placed within the same broader cluster but occupies a separate position, indicating functional divergence while retaining some evolutionary proximity to the query and other taxa.

Branch Length Interpretation:

The relatively short branch lengths connecting the query with P. bursaria Chlorella virus NC1A and E. phage P1 highlight close evolutionary relationships.

While Streptomyces albus G remains within the same cluster, its branch is notably longer, suggesting higher divergence while still maintaining conserved domains with the group.

Functional Insights:

The shared grouping of the query sequence with these taxa, including S. albus G, reinforces the functional relevance of conserved mismatch repair mechanisms.

The divergence of S. albus G within the same cluster may reflect lineage-specific adaptations or partial domain conservation in its MutS protein.

NJ Tree

General Structure and Clustering:

The NJ tree, free from the molecular clock assumption, depicts evolutionary relationships with more flexibility in divergence rates.

The query sequence clusters with P. bursaria Chlorella virus NC1A and E. phage P1, while Streptomyces albus G remains within the same clade but shows a slightly greater degree of separation.

Branch Length Comparison:

The NJ tree captures more variable branch lengths, with S. albus G retaining its position in the same clade but having a longer branch, highlighting divergence from the viral sequences.

The proximity of P. bursaria Chlorella virus NC1A and E. phage P1 to the query sequence aligns with shared evolutionary and functional traits.

Functional Insights:

The consistent clustering of S. albus G within the same group but with greater branch lengths reflects a balance between functional conservation and evolutionary divergence.

As in the UPGMA tree, the close association of the query with viral taxa supports the hypothesis of a conserved role in mismatch repair across diverse organisms.

Key Comparisons Between UPGMA and NJ Trees

Consistency in Clustering:

Both methods place S. albus G within the same clade as the query and viral taxa, reflecting evolutionary proximity despite notable divergence.

The query sequence maintains close clustering with P. bursaria Chlorella virus NC1A and E. phage P1, affirming their strong evolutionary and functional relationships.

Differences in Branch Lengths:

The NJ tree captures more pronounced divergence in branch lengths for S. albus G, while the UPGMA tree simplifies this relationship due to its molecular clock assumption.

Implications of Clustering Patterns:

The stable clustering of the query with viral sequences supports its conserved role in mismatch repair.

The distinct placement of S. albus G within the same broader clade suggests functional variability influenced by its lineage.

Conclusion

The phylogenetic trees consistently place the query sequence with Paramecium bursaria Chlorella virus NC1A and Escherichia phage P1, highlighting strong evolutionary and functional relationships. Streptomyces albus G retains its position within the same clade, emphasizing conserved features while illustrating evolutionary divergence.

These results, aligned with the BLAST findings, demonstrate that the MutS protein retains its core functionality across diverse taxa while accommodating lineage-specific adaptations.

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The pie chart illustrates the predicted secondary structure composition of a protein, divided into three categories: Helices, Sheets, and Turns. Each segment represents a percentage of the overall structure:

1. Secondary Structure Composition

Helices (32.9%): Represented by the pink section, helices are commonly found in globular proteins. These compact and stable structures often contribute to ligand binding and maintaining the protein's structural integrity.

Sheets (35.2%): Shown in blue, beta sheets provide significant structural stability. They are frequently found in structural proteins or enzymes that contain beta-barrel motifs.

Turns (31.9%): Indicated by the green section, turns are flexible regions connecting helices and sheets. They are essential for allowing the polypeptide chain to change direction, aiding in protein folding and structural stability.

2. Structural Importance

The chart's data indicates a composition typical of proteins folding into globular shapes, suitable for aqueous environments where enzymatic reactions and molecular interactions commonly occur. This structural arrangement supports the protein's functional versatility and stability.

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The pie chart illustrates the predicted secondary structure composition of the PtsP protein, divided into three categories: Helices, Sheets, and Turns. Each segment represents a percentage of the overall structure:

1. Secondary Structure Composition

Helices (38.9%): Represented by the pink section, helices form the largest proportion of PtsP's secondary structure. These elements are crucial for providing stability and flexibility, often playing a role in ligand binding and structural integrity.

Sheets (34.8%): Shown in blue, beta sheets form a substantial part of the structure. These rigid elements contribute significantly to the protein's overall stability and are frequently involved in forming structural cores or beta-barrel motifs.

Turns (26.3%): Indicated by the green section, turns connect helices and sheets. While they are the smallest component, turns play a critical role in facilitating the protein's folding and enabling the chain to adapt its conformation.

2. Structural Importance

The chart suggests a structure characteristic of globular proteins, optimized for aqueous environments where PtsP operates. This configuration balances stability and adaptability, essential for its role in facilitating phosphotransfer reactions and coordinating with other proteins in the PTS system.

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In this section, you can find explained with clarity the contributions of each element of the group to this project.

The main function of this project was the individual assignment of genes to each team member, allowing for a specific and in-depth approach for each case:

Catarina Gomes was responsible for studying the FAEPRAM212_RS11550 gene.

Maria Carvalho worked on the ptsP gene.

Muneeb Mohammad concentrated on the FAEPRAM212_03428 gene, using a distinct approach, adapted to his interpretative process.

Throughout this project, there was an efficient division of tasks between Catarina and Maria. Catarina focused predominantly on the creation and maintenance of the GitHub repository, while Maria took charge of building and organizing the interpretation of the content on Padlet, and the content of the presentation. Despite this primary division, both actively participated in all stages, collaborating closely to ensure the success of the tasks.

Muneeb initially opted for a slightly different coding approach, making adjustments in specific branches to align with his interpretation. He also contributed to the graphical support for protein analysis. However, after receiving feedback, he chose not to proceed with the necessary adjustments, considering his part completed. As a result, the remaining team members had to take over the final analysis of his assigned gene and correct general issues in the code. Catarina and Maria took on this additional workload, ensuring that all required analyses and corrections were completed.

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The pie chart illustrates the predicted secondary structure composition of the MutS Domain I protein, divided into three categories: Helices, Sheets, and Turns.

1. Secondary Structure Composition

Helices (36.6%): Highlighted in pink, helices make up the largest portion of the structure. They provide both stability and flexibility, often contributing to ligand binding and maintaining the structural integrity of the protein.

Sheets (34.9%): Represented in blue, beta sheets form a significant part of the protein. These rigid structures are key to the protein’s overall stability.

Turns (28.5%): Shown in green, turns are the smallest component but play an essential role. They link helices and sheets, aiding in proper folding and allowing the protein to adapt its shape as needed

2. Structural Importance

It looks like the data in the chart shows that this protein fold into globular shape, which makes sense for proteins that function in watery environments. This kind of structure is ideal for things like enzymatic reactions and molecular interactions, helping the protein stay stable and do a variety of jobs effectively.

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Highest Abundance:

Alanine (A)

Glycine (G)

Valine (V)

Lowest Abundance:

Tryptophan (W)

Cysteine (C)

Histidine (H)

Implications:

Structural flexibility is emphasized by the abundance of alanine and glycine, suggesting dynamic regions for folding or conformational changes.

Stability is maintained through hydrophobic interactions, indicated by valine’s prevalence and low cysteine content.

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Bioinformatics Laboratories project promotes the advanced use of bioinformatics tools to analyze a set of genes and sequences of interest from microorganisms in the human intestinal microbiome. - LB_project/results/figures/protein at protein_analysis · cgomes03/LB_project

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MutS Domain I - Predicted phosphorylation sites

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MutS Domain I - Predicted phosphorylation sites

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NetPhos analysis predicts potential phosphorylation sites across the EEU95773.1 sequence.

Serine Phosphorylation Sites -->
numerous serine residues throughout the protein sequence are predicted as phosphorylation candidates. This suggests that the protein undergoes significant regulation through serine kinase activity.

Threonine Phosphorylation Sites -->
Threonine residues also exhibit potential phosphorylation, indicating additional regulatory mechanisms. These may contribute to functional diversification or protein-protein interactions.

Distribution of Phosphorylation Sites --> Phosphorylation potential is observed across the sequence but certain regions show higher clustering. These regions may represent functional domains requiring phosphorylation for activity modulation or protein complex assembly.

The phosphorylation profile of EEU95773.1 highlights its potential as a dynamically regulated protein. These PTMs may influence its functional role in cellular processes such as DNA repair, metabolism, or environmental adaptation.

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MutS Domain I- Interaction with other proteins

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MutS Domain I- Interaction with other proteins

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STRING analysis reveals EEU95773.1 as a key player in protein-protein interaction networks, with strong functional associations linked to DNA repair, metabolism, and regulatory mechanisms.

mutL: DNA mismatch repair protein, plays a crucial role in DNA repair and genomic stability.

polA: DNA polymerase I, an essential enzyme in DNA replication and repair, highlights EEU95773.1's potential involvement in replication fidelity and repair coordination.

Hypothetical Proteins (EEU95771.1 and EEU95772.1):
These proteins likely represent unknown but potentially significant pathways linked to EEU95773.1.

This interaction network positions EEU95773.1 as a potential coordinator of cellular adaptation to environmental and metabolic stressors (https://doi.org/10.1016/j.dnarep.2015.11.013).

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No data was identified regarding the gene variants and their biological effects.

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Highest Abundance:

Alanine (A)

Leucine (L)

Aspartic Acid (D)

Lowest Abundance:

Tryptophan (W)

Histidine (H)

Cysteine (C)

Implications:

Structural Stability is emphasized by the high leucine content which highlights a robust hydrophobic core, while alanine ensures structural flexibility.

The low abundance of histidine and tryptophan indicates that catalytic activity and aromatic stabilization are not major functional aspects of the protein.

# data[].attributes.attachment_link.description
Bioinformatics Laboratories project promotes the advanced use of bioinformatics tools to analyze a set of genes and sequences of interest from microorganisms in the human intestinal microbiome. - LB_project/results/figures/protein at protein_analysis · cgomes03/LB_project

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Molecular Weight: ~490 Kilo Daltons (Da)

Aromaticity Index: 0.08

Low proportion of aromatic amino acids (Phenylalanine, Tyrosine, Tryptophan)

Instability Index: 32.10 units

Below 40 units indicates a stable protein

Suggests protein is relatively stable in vitro

Isoelectric Point (pI): 5.54

Acidic protein

Negatively charged at physiological pH (pH 7.4)

# data[].attributes.attachment_link.description
Bioinformatics Laboratories project promotes the advanced use of bioinformatics tools to analyze a set of genes and sequences of interest from microorganisms in the human intestinal microbiome. - LB_project/results/figures/protein at protein_analysis · cgomes03/LB_project

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Molecular Weight: ~600 Kilo Daltons (Da)

Aromaticity Index: 0.06

Low proportion of aromatic amino acids in the protein ( Phenylalanine, Tyrosine, and Tryptophan)

Instability Index: 35.52 units

Below 40 units indicates a stable protein

Suggests protein is relatively stable in vitro

Isoelectric Point (pI): 4.98

Acidic protein

Negatively charged at physiological pH (pH 7.4)

# data[].attributes.attachment_link.description
Bioinformatics Laboratories project promotes the advanced use of bioinformatics tools to analyze a set of genes and sequences of interest from microorganisms in the human intestinal microbiome. - LB_project/results/figures/protein at protein_analysis · cgomes03/LB_project

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Molecular Weight: ~ 300 kilo Daltons (Da)

Aromaticity Index: 0.08

Low proportion of aromatic amino acids (Phenylalanine, Tyrosine, Tryptophan)

Instability Index: 39.04 units

Below 40 units indicates a stable protein

Suggests protein is relatively stable in vitro

Isoelectric Point (pI): 4.96

Acidic protein

Negatively charged at physiological pH (pH 7.4)

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There were 8 alignments found in the BLASTp run, but only 5 were saved due to the parameters set (e_value=0.01, identity=30, coverage=30).

E-value (Top hits ~ 0.00) --> support strong conservation for its primary functional domains. (Lower E-value 9.18e+0) --> matches to eukaryotic organism (Arabidopsis), likely due to conserved but less specific protein domains.

Identity values (Top hits >70%) --> suggesting high conservation among specific bacterial species. (Lower identity matches <40%) --> partial or more distant homology.

Coverage (>95% strongest hits )--> well-matched regions for core functional domains.

Alignments are predominantly with bacterial species known for butyrate metabolism, suggesting functional conservation.

Coverage and identity values are high for key alignments, reflecting strong homologous sequences.

Strong matches were found with Roseburia and Anaerostipes species, likely bacterial strains involved in similar metabolic pathways.

Lower matches (p.e Arabidopsis thaliana) suggest potentially unrelated homologs.

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LB_project/3. Homology Analysis.ipynb at main · cgomes03/LB_project

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Bioinformatics Laboratories project promotes the advanced use of bioinformatics tools to analyze a set of genes and sequences of interest from microorganisms in the human intestinal microbiome. - c…

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There were 50 alignments found in the BLASTp run, but only 45 were saved due to the parameters set (e_value=0.01, identity=30, coverage=30).

E-value (~ 0.00) --> suggest that ptsP is highly conserved and shares well-defined homologous regions with numerous organisms.

Identity values vary, but the presence of 45 alignments suggests that ptsP homologs are broadly distributed, with varying degrees of similarity.

Coverage (>90% for the strongest hits) --> well-conserved regions across sequences.

The high number of alignments suggests the ptsP protein is widely conserved across various organisms, particularly bacteria.

Alignments likely indicate key roles for the ptsP, potentially related to phosphotransferase systems in microbial metabolism.

ptsP aligns with numerous organisms, indicating widespread conservation.

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LB_project/3. Homology Analysis.ipynb at main · cgomes03/LB_project

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Bioinformatics Laboratories project promotes the advanced use of bioinformatics tools to analyze a set of genes and sequences of interest from microorganisms in the human intestinal microbiome. - c…

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There were 7 alignments found in the BLASTp run, but only 3 were saved due to the parameters set (e_value=0.1, identity=15, coverage=5 --> The filtering parameters for BLASTp were different for MutS because, with the initial parameters, it did not produce as many hits).

Identity values (<40%) --> distant evolutionary relationships or partial domain conservation.

Coverage (<20%) --> limited homologous regions or that MutS sequences are highly divergent.

Results show diverse homologous sequences but weaker matches (lower identity and coverage).

The high E-value thresholds suggest potential false positives or distantly related sequences.

Alignments suggest a broad range of homologous sequences across diverse organisms, including phages, viruses, and bacteria.

The relatively lower identity and coverage values indicate weak homologous relationships.

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LB_project/3. Homology Analysis.ipynb at main · cgomes03/LB_project

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Bioinformatics Laboratories project promotes the advanced use of bioinformatics tools to analyze a set of genes and sequences of interest from microorganisms in the human intestinal microbiome. - c…

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Based on the results (No clear conservation patterns, low E-values), we can't confidently say that the motifs are conserved or biologically meaningful. There are no clear patterns of conservation, and the statistical support for the motifs is weak, which makes it doubtful that they have any real biological significance.

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Click on the "+" or "-" buttons to the left of the motif to see the forward or reverse complement of the motif if available.

The statistical significance of the motif. MEME usually finds the most statistically significant (low E-value) motifs first. It is unusual to consider a motif with an E-value larger than 0.05 significant so, as an additional indicator, MEME displays these greyed out.

The E-value of a motif is based on its log likelihood ratio, width, sites, the background letter frequencies (given in the command line summary), and the size of the training set.

The E-value is an estimate of the expected number of motifs with the given log likelihood ratio (or higher), and with the same width and site count, that one would find in a similarly sized set of random sequences (sequences where each position is independent and letters are chosen according to the background letter frequencies).

The strand used for the motif site.

+

The motif site was found in the sequence as it was supplied.

-

The motif site was found in the reverse complement of the supplied sequence.

These are the motif sites predicted by MEME plus any additional sites detected using a motif scanning algorithm.

These MEME sites are shown in solid color and additional scanned sites are shown greyed out. Hovering the cursor over a site will reveal details about the site. Only sequences containing a predicted or scanned motif site are shown.

The scanned sites are predicted using a log-odds scoring matrix constructed from the MEME sites. Only scanned sites with position p-values less than 0.0001 are shown.

This is the combined match p-value.

The combined match p-value is defined as the probability that a random sequence (with the same length and conforming to the background) would have position p-values such that the product is smaller or equal to the value calculated for the sequence under test.

The position p-value is defined as the probability that a random sequence (with the same length and conforming to the background) would have a match to the motif under test with a score greater or equal to the largest found in the sequence under test.

Hovering your mouse over a motif site in the motif location block diagram will show its position p-value and other information about the site.

This diagram shows the location of motif sites.

Each block shows the position and strength of a motif site. The height of a block gives an indication of the significance of the site as taller blocks are more significant. The height is calculated to be proportional to the negative logarithm of the p-value of the site, truncated at the height for a p-value of 1e-10.

For complementable alphabets (like DNA), sites on the positive strand are shown above the line, sites on the negative strand are shown below.

Placing the cursor over a motif site will reveal more information about the site including its position p-value. (See the help for the p-value column for an explanation of position p-values.)

Discovered Motifs

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Motif Locations

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Inputs & Settings

Sequences

Background Model

Other Settings

Motif Site Distribution

ZOOPS: Zero or one site per sequence OOPS: Exactly one site per sequence ANR: Any number of sites per sequence

Objective Function

Starting Point Function

Site Strand Handling

This alphabet only has one strand Sites must be on the given strand Sites may be on either strand

Maximum Number of Motifs

Motif E-value Threshold

Minimum Motif Width

Maximum Motif Width

Minimum Sites per Motif

Maximum Sites per Motif

Bias on Number of Sites

Sequence Prior

Simple Dirichlet Dirichlet Mixture Mega-weight Dirichlet Mixture Mega-weight Dirichlet Mixture Plus Add One

Sequence Prior Source

Sequence Prior Strength

EM Starting Point Source

From substrings in input sequences From strings on command line (-cons)

EM Starting Point Map Type

Uniform Point Accepted Mutation

EM Starting Point Fuzz

EM Maximum Iterations

EM Improvement Threshold

Maximum Search Size

Maximum Number of Sites for E-values

Trim Gap Open Cost

Trim Gap Extend Cost

End Gap Treatment

No cost Same cost as other gaps

Show Advanced Settings Hide Advanced Settings

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Click on the "+" or "-" buttons to the left of the motif to see the forward or reverse complement of the motif if available. The statistical significance of the motif. MEME usually finds the most statistically significant (low E-value) motifs first.

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Biological Analysis Support Websites

1. NCBI (National Center for Biotechnology Information) – A comprehensive resource for genetic and biomedical research.
🔗 NCBI

2. UniProt (Universal Protein Resource) – A curated database of protein sequence and functional information.
🔗 UniProt

3. PSORTb – A tool for predicting bacterial protein subcellular localization.
🔗 PSORTb

4. InterPro – A resource for protein classification and functional annotation.
🔗 InterPro

5. AlphaFold – An AI-based tool for protein structure prediction developed by DeepMind.
🔗 AlphaFold

6. Phobius – A combined transmembrane topology and signal peptide predictor.
🔗 Phobius

7. Health Tech Services (DTU) – A collection of bioinformatics tools for protein analysis.
🔗 Health Tech

8. STRING (Search Tool for the Retrieval of Interacting Genes/Proteins) – A database of known and predicted protein-protein interactions.
🔗 STRING

9. MEME Suite – A toolkit for motif-based sequence analysis, including motif discovery and scanning.
🔗 MEME

Bioinformatics Modules Used

Biopython – A powerful library for computational biology, enabling sequence analysis, structure handling, and more.

BLAST (Basic Local Alignment Search Tool) – A widely used algorithm for comparing biological sequences.

ClustalW – A tool for multiple sequence alignment to identify evolutionary relationships.

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This GitHub repository was created to support the development of our project, providing essential tools, scripts, and workflows for biological analysis.

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GitHub - cgomes03/LB_project: Bioinformatics Laboratories project promotes the advanced use of bioinformatics tools to analyze a set of genes and sequences of interest from microorganisms in the human intestinal microbiome.

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Bioinformatics Laboratories project promotes the advanced use of bioinformatics tools to analyze a set of genes and sequences of interest from microorganisms in the human intestinal microbiome. - c…