Recombinant Bartonella tribocorum Prolipoprotein diacylglyceryl transferase (lgt)

Basic Research Questions

Advanced Research Questions

• What evidence exists for lateral gene transfer (LGT) of lgt or other virulence factors among Bartonella species?

  Multiple studies have demonstrated that Bartonella species engage in lateral gene transfer despite their intracellular lifestyle. Particularly relevant findings include:

  • B. grahamii shows high recombination rates and evidence of LGT, with genetic exchanges occurring between different strains that share rodent hosts

  • LGT has been observed between B. grahamii and B. taylorii, two species that frequently co-infect the same hosts

  • The Type IV secretion system (T4SS) genes, critical for intracellular viability, show evidence of LGT among bacteria living in phagocytic protists

  • Amoebae may serve as a "melting pot" facilitating gene transfer between Bartonella species and other bacteria including Rhizobiales

  While lgt specifically has not been confirmed as a frequently transferred gene, the evidence of extensive gene exchange among Bartonella species suggests that genes involved in host adaptation, including those for membrane proteins, could be subject to LGT events .

• How can researchers differentiate between homologous recombination and multiple infections when analyzing Bartonella sequence data?

  Differentiating between homologous recombination and multiple infections presents a significant challenge in Bartonella research. Based on the literature, the following methodological approaches are recommended:

  1. Multi-locus sequence analysis: Sequencing multiple genetic loci (gltA, groEL, rpoB, ftsZ, and ITS) can reveal inconsistencies between gene phylogenies that may indicate recombination events

  2. Examination of sequence chromatograms: Multiple peaks in chromatograms may indicate mixed infections, though not all cases of multiple infections show this pattern due to varying DNA abundances

  3. Cloning before sequencing: When conflicts between loci are detected or multiple peaks are observed, cloning sequences into vectors before sequencing can help differentiate between scenarios

  4. Deep sequencing approaches: These can provide better resolution to detect low-abundance variants that may be missed in consensus sequences

  As observed in studies of rodent bartonellae from Benin, conflicts between gltA and rpoB sequences were found, with one locus indicating B. elizabethae and the other indicating B. tribocorum, highlighting the challenges in distinguishing between recombination and co-infection .

• What experimental systems are optimal for studying horizontal gene transfer mechanisms in Bartonella species?

  Based on current research, several experimental systems have proven effective for studying horizontal gene transfer in Bartonella:

  1. Amoeba co-culture systems: Evidence suggests that amoebae (particularly Acanthamoeba polyphaga) can serve as "melting pots" where different bacterial species co-exist and exchange genetic material. This system has successfully demonstrated conjugation between B. rattaustraliani and Rhizobium radiobacter

  2. In vitro conjugation assays: Systems designed to detect the transfer of plasmids containing markers such as the Type IV secretion system genes

  3. Phylogenetic analysis paired with Bayesian ancestral state reconstruction: This computational approach can detect historical gene transfer events and assess their relationship to host switches

  4. Multi-locus sequence typing (MLST): This method balances the tradeoffs of culturing bias, phylogenetic resolution, homologous recombination detection, and gene conservation across species

  The combination of these experimental and computational approaches provides a comprehensive framework for investigating horizontal gene transfer in Bartonella species.

Methodological Questions

• What expression systems yield the highest quality recombinant B. tribocorum lgt protein?

  Based on available information, E. coli expression systems have been successfully used to produce recombinant B. tribocorum lgt protein . The following methodological considerations are important:

  • Expression vector selection: Systems incorporating N-terminal tags (such as 10xHis) have been successfully used

  • Expression conditions: While specific optimization parameters aren't detailed in the literature for B. tribocorum lgt, typical considerations include:

    • Induction temperature (often lowered to 16-25°C for membrane proteins)

    • Inducer concentration

    • Expression duration

  • Protein extraction: Given that lgt is a transmembrane protein, appropriate detergent-based extraction methods are necessary

  The recombinant protein produced in E. coli systems has been used successfully for applications including ELISA development .

• What are the optimal storage conditions for maintaining lgt stability and activity?

  Based on product information for recombinant B. tribocorum lgt, the following storage recommendations apply:

  • Short-term storage: Working aliquots can be stored at 4°C for up to one week

  • Long-term storage: Store at -20°C; for extended storage, conserve at -20°C or -80°C

  • Buffer composition: Tris-based buffer with 50% glycerol, optimized for this protein

  • Freeze-thaw cycles: Repeated freezing and thawing is not recommended

  For lyophilized preparations, the shelf life is approximately 12 months at -20°C/-80°C, while liquid preparations typically have a shelf life of 6 months under the same conditions .

• What methods are most effective for assessing the enzymatic activity of recombinant B. tribocorum lgt?

  While specific activity assays for B. tribocorum lgt are not detailed in the provided literature, approaches used for lgt from related bacteria can be adapted:

  1. Radiometric assays: Using radiolabeled substrates such as 14C-palmitate to measure lipid incorporation into prolipoproteins, similar to the approach used with B. anthracis lgt

  2. Substrate conversion assays: Monitoring the conversion of prolipoproteins to lipoproteins using techniques such as:

     • Gel mobility shift assays

     • Mass spectrometry to detect lipid modifications

  3. Complementation assays: Testing whether B. tribocorum lgt can restore function in lgt-deficient bacterial strains

  When developing activity assays, researchers should consider that lgt transfers the diacylglyceryl moiety from phosphatidylglycerol to the sulfhydryl group of the invariant cysteine in the lipobox of prolipoproteins, which requires appropriate substrate selection and reaction conditions.

Data Analysis and Interpretation Questions

• How should researchers interpret phylogenetic conflicts in multi-gene analyses of Bartonella species?

  When encountering conflicting phylogenetic signals across different genes in Bartonella studies, researchers should consider the following analytical approaches:

  1. Evaluate evidence for recombination: Use computational methods to detect recombination breakpoints and assess recombination rates between different Bartonella lineages

  2. Consider multiple infection scenarios: Especially when working with field samples, conflicts between gene trees may indicate the presence of multiple Bartonella species rather than recombination

  3. Apply global fit methods: These techniques test for congruence between parasite phylogeny and host phylogeny or host range overlap, accounting for the confounding factors that some hosts carry multiple Bartonella genotypes and some Bartonella genotypes infect multiple hosts

  4. Use Bayesian ancestral state reconstruction: This approach can simultaneously reconstruct phylogeny, count discrete state changes, and estimate the likelihood of different evolutionary models, helping to distinguish between codivergence with hosts, parasite phylogeography, and adaptation to hosts/vectors

  In specific cases like that observed with Bartonella from rodents in Benin, where gltA indicated B. elizabethae and rpoB indicated B. tribocorum, researchers should acknowledge both recombination and multiple infection as potential explanations .

• What bioinformatic approaches are recommended for analyzing the evolutionary history of lgt in Bartonella species?

  Several bioinformatic approaches have been successfully applied to analyze the evolutionary history of Bartonella genes, which can be adapted for lgt analysis:

  1. Bayesian phylogenetic analysis: This approach has been used to infer the evolutionary history of Bartonella species, with good convergence and effective sample size (ESS) for parameter estimates (>200)

  2. Ancestral state reconstruction: This method can reveal patterns of host shifts and geographic dispersal of Bartonella lineages over time

  3. Molecular clock analyses: These can help estimate divergence times and correlate them with historical events, such as human exploration or colonization events that might have facilitated Bartonella dispersal via rats

  4. Detection of selection signatures: Analysis of non-synonymous to synonymous substitution ratios can identify regions of proteins under purifying or diversifying selection

  5. Comparative genomics: Analysis of synteny and gene content across multiple Bartonella genomes can provide insights into the conservation and potential horizontal transfer of lgt

  When applying these methods to lgt specifically, researchers should consider that full-genome analyses are preferable to avoid confounding by lateral gene transfer and recombination events that might affect individual genes .

• What approaches can be used to predict the potential substrates of B. tribocorum lgt?

  Predicting potential substrates of B. tribocorum lgt involves several complementary approaches:

  1. Lipoprotein prediction algorithms: Computational tools like LipoP, DOLOP, or SignalP can be used to scan the B. tribocorum genome for sequences containing the lipobox motif (typically [LVI][ASTVI][GAS][C]) that marks prolipoproteins as lgt substrates

  2. Comparative proteomics: Analysis of lipoproteins identified in related Bartonella species can help identify conserved substrates likely to be present in B. tribocorum

  3. Experimental verification: Methods including:

     • Palmitate labeling in wild-type versus lgt-knockout strains to identify lipoproteins dependent on lgt activity

     • Mass spectrometry-based proteomics to identify lipid-modified proteins

     • Membrane fractionation to isolate and identify lipoproteins

  4. Functional prediction: Bioinformatic analysis of identified potential substrates to predict their functions in processes such as:

     • Nutrient acquisition

     • Cell wall maintenance

     • Host cell interaction

     • Immune evasion

  Understanding the substrate range of lgt is crucial for comprehending its role in Bartonella pathogenesis and adaptation to diverse host environments.