Recombinant Synechocystis sp. tRNA (guanine-N (1)-)-methyltransferase

What is tRNA (guanine-N(1)-)-methyltransferase and what is its primary function in Synechocystis sp.?

tRNA (guanine-N(1)-)-methyltransferase (EC 2.1.1.31) is an enzyme that catalyzes the methylation of guanine at the N1 position in tRNA molecules. The reaction specifically involves the transfer of a methyl group from S-adenosyl-L-methionine (SAM) to tRNA, resulting in the formation of S-adenosyl-L-homocysteine and tRNA containing N1-methylguanine . In Synechocystis sp., this post-transcriptional modification of tRNA is essential for maintaining proper tRNA structure and function, which directly impacts the fidelity and efficiency of protein translation. The enzyme belongs to the family of transferases, specifically those that transfer one-carbon group methyltransferases .

What are the key structural characteristics of tRNA (guanine-N(1)-)-methyltransferase that enable its catalytic function?

tRNA (guanine-N(1)-)-methyltransferase possesses a characteristic methyltransferase domain structure with a SAM-binding region and a substrate-binding pocket specific for tRNA. While the search results don't provide detailed structural information for this specific enzyme in Synechocystis sp., the enzyme's classification (EC 2.1.1.31) indicates it belongs to the well-characterized family of S-adenosyl-L-methionine-dependent methyltransferases . These enzymes typically feature a Rossmann fold for SAM binding and specialized domains for recognizing and binding specific tRNA substrates. The enzyme must recognize not only the guanine base to be methylated but also the structural context within the tRNA molecule, ensuring specific modification at the N1 position. X-ray crystallography and structural studies would be needed to determine the precise three-dimensional structure of the Synechocystis variant.

How might tRNA methyltransferase activity in Synechocystis sp. be affected during metabolic engineering for bioproduct synthesis?

When Synechocystis sp. is metabolically engineered for bioproduct synthesis (such as ethanol or polyhydroxyalkanoate production), significant transcriptional remodeling occurs. Research shows that under conditions promoting PHA accumulation, recombinant Synechocystis strains exhibit upregulation of photosynthesis-related genes but downregulation of genes involved in protein metabolism, cofactor synthesis, and vitamin metabolism . For tRNA methyltransferases, this shifting metabolic landscape would likely result in changed expression patterns and potentially altered activity levels. The redirection of cellular resources toward bioproduct synthesis may reduce the availability of S-adenosyl-L-methionine, the methyl donor required for tRNA methylation . Additionally, changes in tRNA methylation patterns could affect the translation efficiency of specific codons, potentially impacting the expression of introduced recombinant pathways or native metabolic functions.

What transcriptomic changes correlate with tRNA methyltransferase activity during nitrogen deficiency in recombinant Synechocystis sp.?

Under nitrogen deficiency conditions, recombinant Synechocystis sp. strains engineered for PHA production show distinct transcriptomic signatures. While specific data on tRNA methyltransferase expression is not provided in the search results, related gene expression patterns can inform our understanding. Highly efficient PHA-producing strains (CCsACnBCn and CCsNphT7BCn) show significant upregulation of genes involved in photosynthesis, transport, and cell communication compared to reference strains . Notably, photosystem I reaction center subunits (psaM and psaJ) show 12-22 fold increases in expression . Conversely, these strains show decreased expression of genes involved in cofactor metabolism, vitamin synthesis, and protein metabolic processes . These patterns suggest that during nitrogen deficiency, Synechocystis sp. prioritizes certain metabolic functions while downregulating others, which would likely include adjustments to tRNA modification processes to optimize translation under stress conditions.

How does the integration of heterologous tRNA methyltransferases impact the translational machinery and codon usage in recombinant Synechocystis sp.?

The integration of heterologous tRNA methyltransferases into Synechocystis sp. would likely have multifaceted effects on the translational machinery. While the search results don't directly address this specific question, insights can be drawn from related research on recombinant protein expression in this organism. In recombinant Synechocystis strains with increased PHA production capabilities, genes encoding heterologous proteins showed varying expression levels, with some showing up to 3-fold lower expression compared to others despite being on the same operon . This suggests that codon optimization and translational efficiency are critical factors affecting heterologous gene expression.

Introducing foreign tRNA methyltransferases could potentially alter the modification status of specific tRNA molecules, thereby changing their ability to decode certain codons efficiently. This could have downstream effects on the expression of both native and recombinant genes, particularly those with codon usage patterns that depend on the modified tRNAs. The data from recombinant Synechocystis strains indicates that expression levels of introduced genes can vary significantly even when they are located on the same operon, highlighting the complex interplay between gene expression, translation, and potentially tRNA modifications .

What are the optimal experimental approaches for measuring tRNA (guanine-N(1)-)-methyltransferase activity in recombinant Synechocystis sp.?

Measuring tRNA (guanine-N(1)-)-methyltransferase activity in recombinant Synechocystis sp. requires a combination of biochemical and molecular approaches. The most direct method involves enzyme activity assays using purified enzyme and appropriate substrates. Based on the enzyme's known catalytic function, a typical assay would monitor the transfer of a methyl group from S-adenosyl-L-methionine to tRNA substrates .

The recommended protocol would involve:

• Expression and purification of the recombinant enzyme

• Preparation of substrate tRNA (either synthetic or purified from cells)

• Incubation of the enzyme with tRNA and radiolabeled S-adenosyl-L-methionine

• Detection of methylated tRNA products

Alternatively, researchers can employ liquid chromatography-mass spectrometry (LC-MS) to detect and quantify the modified nucleosides in tRNA extracted from cells. This approach allows for monitoring the in vivo activity of the methyltransferase under various experimental conditions. RNA-seq technologies, similar to those used in the photoautotrophic PHA accumulation studies, can also be employed to analyze the transcriptional responses associated with methyltransferase expression and activity .

What techniques are most effective for analyzing the impact of tRNA methylation on codon-specific translation efficiency in Synechocystis sp.?

To analyze the impact of tRNA methylation on codon-specific translation efficiency in Synechocystis sp., researchers should employ a multi-faceted approach combining ribosome profiling, reporter gene assays, and mass spectrometry-based techniques.

Ribosome profiling provides a genome-wide view of translation by capturing the positions of ribosomes on mRNAs. This technique can reveal codon-specific pausing or enhanced translation that may result from altered tRNA methylation patterns. For targeted analysis, reporter gene constructs containing specific codons of interest can be used to quantitatively assess how tRNA methylation affects the expression of these constructs.

Mass spectrometry analysis of tRNA can precisely identify and quantify modified nucleosides, enabling direct correlation between methylation status and translation efficiency. When analyzed alongside RNA-seq data (similar to the approach used in the PHA accumulation studies), researchers can correlate changes in methyltransferase expression with broader transcriptomic adaptations .

The experimental design should include:

• Creation of methyltransferase knockout, overexpression, and wild-type strains

• Ribosome profiling under various growth conditions

• Reporter gene assays with codon-biased constructs

• LC-MS/MS analysis of tRNA modifications

• Integration of data to identify codon-specific translation effects

How can RNA-seq data be effectively analyzed to identify correlations between tRNA methyltransferase expression and global transcriptional responses?

RNA-seq data analysis for identifying correlations between tRNA methyltransferase expression and global transcriptional responses should follow a systematic workflow. Based on the approaches used in the recombinant Synechocystis sp. studies, the recommended methodology would include:

• Data Quality Assessment and Normalization: Evaluate sequencing quality and normalize read counts to RPKM (Reads Per Kilobase of transcript per Million mapped reads) as demonstrated in the PHA accumulation studies .

• Differential Expression Analysis: Identify genes with significant expression changes between experimental conditions. The PHA accumulation study revealed correlation coefficients between biological replicates of 0.96-0.98, indicating high reproducibility .

• Functional Categorization: Group differentially expressed genes into functional categories. The PHA studies identified distinct patterns where photosynthesis genes were upregulated while metabolic process genes were downregulated .

• Correlation Analysis: Calculate correlation coefficients between tRNA methyltransferase gene expression and other genes to identify potentially co-regulated genes.

• Pathway Enrichment Analysis: Determine which biological pathways are significantly enriched among correlated genes. This approach revealed that in PHA-producing strains, genes involved in photosynthesis, transport, and cell communication were significantly enriched among upregulated genes .

• Integration with Other Omics Data: Combine RNA-seq data with proteomics, metabolomics, or tRNA modification profiles to develop a comprehensive understanding of the system.

The example from the PHA accumulation study shows that RNA-seq analysis successfully identified gene expression patterns correlating with increased PHA production, highlighting genes such as psaM, psaJ, psbX, and psbK that were upregulated more than 5-fold in high-producing strains .

What strategies can be employed to optimize expression and activity of recombinant tRNA (guanine-N(1)-)-methyltransferase in Synechocystis sp.?

Optimizing expression and activity of recombinant tRNA (guanine-N(1)-)-methyltransferase in Synechocystis sp. requires careful consideration of several factors. Based on the experiences with other recombinant proteins in Synechocystis, the following strategies are recommended:

• Promoter Selection: Choose appropriate promoters for consistent expression. The PHA synthesis studies showed that gene expression levels can vary significantly depending on the genetic context, with some genes showing 2-fold lower expression levels despite being on the same operon .

• Codon Optimization: Adapt the coding sequence to Synechocystis sp. codon usage preferences. The RNA-seq data from PHA-producing strains revealed that translation-related genes are differentially regulated under stress conditions, suggesting the importance of codon optimization .

• Expression Timing: Consider using inducible promoters to control expression timing. The transcriptomic data from nitrogen-deficient conditions showed that the cellular response to stress involves complex transcriptional remodeling .

• Integration Site Selection: Choose genomic integration sites carefully. The PHA studies demonstrated that genes introduced into different locations in the Synechocystis genome showed varying expression levels .

• Co-factor Availability: Ensure sufficient availability of S-adenosyl-L-methionine, the methyl donor required for methyltransferase activity .

• Growth Condition Optimization: Fine-tune cultivation conditions. The study of recombinant Synechocystis strains showed that nitrogen deficiency combined with 5% CO2 led to optimal PHA production (25-30% of dry cell weight) .

A monitoring system using reporter genes or activity assays should be established to track expression and activity during optimization experiments. The approach used in the PHA accumulation studies, combining targeted gene expression analysis with global transcriptomic profiling, provides a useful template for this optimization process .

How does tRNA methylation status correlate with transcriptomic changes during ethanol production in recombinant Synechocystis sp.?

During ethanol production in recombinant Synechocystis sp., significant transcriptomic changes occur that may correlate with tRNA methylation patterns. Studies have shown that in ethanol-producing strains, specific genes show differential expression compared to wild-type strains. For instance, photosystem I subunit PsaC showed significantly decreased mRNA levels (log2 fold change of -0.92 at day 11 and -1.15 at day 18) in ethanol producers . While the search results don't directly address tRNA methylation in this context, the observed transcriptomic changes suggest alterations in translational regulation.

The differential processing of specific mRNAs, such as the cpcBA mRNA, which showed specific reduction in cpcB levels while cpcA remained stable, indicates complex post-transcriptional regulatory mechanisms are active during ethanol production . This pattern of selective mRNA processing could potentially be influenced by changes in tRNA modification status, as altered tRNA methylation could affect translation efficiency of specific codons and thereby influence protein synthesis rates. The observed accumulation of a truncated cpcA* transcript that lacks a start codon further points to intricate post-transcriptional and translational regulation mechanisms that could involve tRNA modifications .

What is the relationship between tRNA methyltransferase activity and PHA accumulation in engineered Synechocystis sp. strains?

In engineered Synechocystis sp. strains capable of accumulating polyhydroxyalkanoates (PHA), significant transcriptional changes occur that may intersect with tRNA methylation processes. The recombinant strains CCsACnBCn and CCsNphT7BCn, which accumulated higher levels of PHA (10-25% of dry cell weight) compared to control strains, showed distinct transcriptomic signatures .

While specific data on tRNA methyltransferase expression isn't provided in the search results, related observations offer valuable insights. These high-PHA-producing strains exhibited upregulation of genes involved in photosynthesis, transport, and cell communication, while genes involved in protein metabolism and cofactor synthesis were downregulated . This metabolic redistribution likely affects the expression and activity of tRNA modification enzymes.

Particularly notable was the observation that despite higher PHA accumulation in strain CCsNphT7BCn, the expression levels of most PHA synthesis-related genes in this strain were relatively lower compared to other strains . This apparent discrepancy suggests that factors beyond mere transcript abundance, such as translational efficiency (potentially influenced by tRNA modifications), play important roles in determining enzyme activity and metabolic output.

What insights can be gained from comparing tRNA methylation patterns between different recombinant Synechocystis sp. strains under nitrogen deficiency?

Comparison of different recombinant Synechocystis sp. strains under nitrogen deficiency reveals significant differences in gene expression patterns that may extend to tRNA methylation processes. The RNA-seq data from strains with different PHA-producing capabilities showed that the cellular response to nitrogen deficiency involves complex transcriptional remodeling .

The table below summarizes key gene expression differences observed between high-PHA-producing strains compared to reference strains under nitrogen deficiency:

Additionally, when comparing between the two high-producing strains, several genes showed differential expression:

These expression patterns reflect the cellular adaptation to nitrogen deficiency and the metabolic burden of PHA production . While tRNA methyltransferases aren't specifically mentioned in these datasets, the general downregulation of protein metabolism genes suggests potential changes in tRNA modification processes, which could in turn affect translation efficiency of specific transcripts. The differential expression of chaperones and proteases between high-producing strains further suggests variations in post-transcriptional and post-translational regulatory mechanisms that might be influenced by tRNA modification status.

How might CRISPR-Cas9 technologies be optimally applied to study tRNA (guanine-N(1)-)-methyltransferase function in Synechocystis sp.?

CRISPR-Cas9 technologies offer powerful approaches to study tRNA (guanine-N(1)-)-methyltransferase function in Synechocystis sp. through precise genome editing. For effective application, researchers should consider a multi-faceted approach that enables both loss-of-function and gain-of-function studies.

For knockout studies, CRISPR-Cas9 can be employed to create precise deletions or insertions in the methyltransferase gene. When designing guide RNAs, researchers should target conserved catalytic domains identified through comparison with the characterized enzyme (EC 2.1.1.31) . Complete knockouts may be lethal if the methylation is essential, so creating conditional knockdowns through inducible promoter replacement might be more informative.

For gain-of-function studies, CRISPR can facilitate precise integration of modified methyltransferase variants or heterologous methyltransferases. This approach could be particularly valuable for investigating how specific structural features contribute to substrate specificity or catalytic efficiency. Based on the expression patterns observed in recombinant Synechocystis strains, integration sites should be carefully selected to ensure stable expression .

Additionally, CRISPR base editing technologies could enable the creation of point mutations to study structure-function relationships without completely disrupting the enzyme. This would be particularly valuable for investigating the SAM-binding domain and catalytic residues essential for methyl transfer reactions .

What methodological approaches would best elucidate the impact of environmental factors on tRNA methylation dynamics in Synechocystis sp.?

To elucidate the impact of environmental factors on tRNA methylation dynamics in Synechocystis sp., a comprehensive methodological approach combining molecular, analytical, and systems biology techniques is recommended.

Time-course experiments should be designed to capture dynamic changes in tRNA methylation patterns under various environmental conditions (light intensity, temperature, nutrient availability, and stress factors). Based on the transcriptomic studies of nitrogen-deficient conditions, nitrogen limitation represents a particularly relevant stress condition for investigation .

High-throughput analytical techniques, including liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS), should be employed to quantitatively profile tRNA modifications across conditions. This approach allows for comprehensive characterization of modification patterns and can detect even subtle changes in methylation status.

RNA-seq analysis, similar to that used in the PHA accumulation studies, should be conducted in parallel to correlate changes in methyltransferase expression with broader transcriptomic responses . The high reproducibility demonstrated in previous RNA-seq studies (correlation coefficients of 0.96-0.98 between biological replicates) suggests this approach would provide reliable data on transcriptional responses .

Proteomics approaches should complement the transcriptomic data to account for post-transcriptional regulation. The discrepancies observed between transcript levels and PHA accumulation in recombinant Synechocystis strains highlight the importance of examining protein levels in addition to mRNA abundance .

Finally, integrative computational modeling should be used to synthesize the multi-omics data and identify key regulatory relationships between environmental factors, methyltransferase activity, and cellular phenotypes.

How does our understanding of tRNA (guanine-N(1)-)-methyltransferase contribute to the broader field of cyanobacterial synthetic biology?

Understanding tRNA (guanine-N(1)-)-methyltransferase in Synechocystis sp. contributes significantly to cyanobacterial synthetic biology by illuminating crucial aspects of translational regulation. As demonstrated by studies of recombinant Synechocystis strains, successful metabolic engineering requires not only the introduction of heterologous pathway genes but also consideration of how these modifications impact the host's cellular machinery .

tRNA methylation represents a critical layer of translational control that can influence the expression efficiency of both native and recombinant genes. The enzyme's role in catalyzing the transfer of methyl groups from S-adenosyl-L-methionine to specific positions in tRNA molecules directly affects tRNA structure and function . This, in turn, impacts codon-anticodon interactions and ultimately the efficiency and accuracy of protein synthesis.

Research on PHA-producing recombinant Synechocystis strains revealed that despite higher PHA accumulation in strain CCsNphT7BCn, the expression levels of most PHA synthesis-related genes were relatively lower compared to other strains . This apparent discrepancy highlights the importance of post-transcriptional factors, potentially including tRNA modifications, in determining the actual output of metabolic pathways.

Furthermore, the observed transcriptomic remodeling in response to nitrogen deficiency and recombinant protein expression provides valuable insights into how cyanobacteria adapt their translational machinery to different conditions . Understanding these adaptations, including potential changes in tRNA modification patterns, will be essential for designing more efficient and robust synthetic biology applications using cyanobacterial hosts.