# Troubleshooting Common Errors in Microbial Genome Submission to ENA ## Quick Answer - Resolve ENA submission errors by validating FASTA and FASTQ format compliance, completing all mandatory metadata fields, and checking assembly file formatting before upload. - Use the ENA Webin submission portal validation tools to identify specific errors, then correct files locally and resubmit instead of editing within the portal. - Important limitation: ENA validation rules change with each release, so consult the current ENA documentation for the latest requirements before submission. ## Understanding ENA Submission Requirements The European Nucleotide Archive (ENA) serves as one of the three major international nucleotide sequence databases, alongside GenBank and the DNA Data Bank of Japan. These three repositories exchange data daily through the International Nucleotide Sequence Database Collaboration, meaning that a submission to ENA becomes accessible through all partner databases. For bacterial genome researchers, ENA submission is often a prerequisite for publication, grant compliance, and public health surveillance reporting. The submission process requires researchers to provide both sequence data and contextual metadata. Sequence data includes the raw reads from sequencing platforms, typically in FASTQ format, and the assembled genome, typically in FASTA format. Metadata includes information about the organism, the isolation source, the geographic location, the collection date, and the sequencing platform used. The ENA Webin submission system validates these files against a set of rules that check for format compliance, data consistency, and completeness of required fields. Common errors in ENA submission fall into several categories. Format errors occur when files do not conform to the expected structure, such as incorrect FASTA headers or malformed FASTQ quality scores. Metadata errors occur when required fields are missing, incorrectly formatted, or inconsistent with the sequence data. Assembly errors occur when the assembly file contains contigs that do not match the expected format or when the assembly has been improperly annotated. Sample errors occur when the sample metadata does not meet the checklist requirements for the specific project type. Understanding the submission pipeline is essential for troubleshooting. The ENA submission process involves registering a study, registering samples, submitting raw reads, and submitting assembled genomes. Each step has its own validation requirements, and errors at one step can prevent progress to the next. The Webin submission system provides error messages that describe the problem and often include the specific field or file that needs correction. ## At a Glance | Error Category | Common Cause | Practical Fix | Prevention | | --- | --- | --- | --- | | FASTA format errors | Incorrect header lines, invalid characters, or missing sequence lines | Reformat headers to match the pattern `>contig_name` with no spaces or special characters | Use a sequence validation script before submission | | Missing mandatory metadata | Required fields left blank in the sample registration form | Complete all fields marked as mandatory in the Webin submission interface | Prepare a metadata spreadsheet before starting the submission | | Assembly file errors | Contigs not sorted by size, or sequence identifiers not matching the assembly report | Sort contigs by length and verify identifiers match the manifest | Use the ENA assembly validation tool before upload | | FASTQ quality score errors | Quality scores encoded in the wrong Phred scale | Convert quality scores to the expected Phred encoding | Confirm the sequencing platform output format before conversion | | Sample registration conflicts | Duplicate sample names or mismatched taxonomy | Rename samples and verify taxonomy against the NCBI taxonomy database | Use unique sample identifiers and check taxonomy before registration | ## Preparing Files for Submission ### FASTA File Format Requirements The FASTA format is the standard for nucleotide sequence data in ENA submissions. Each record in a FASTA file begins with a header line that starts with the greater-than symbol, followed by the sequence identifier and optional description. The sequence lines follow the header and contain only the nucleotide characters A, C, G, T, and N for ambiguous bases. The ENA validation system rejects files with headers that contain spaces, special characters, or duplicate identifiers. For bacterial genome assemblies, the FASTA file should contain the complete set of contigs or scaffolds that make up the genome. The header line should include a unique identifier for each contig, and the sequence lines should be wrapped at a consistent line length, typically 60 to 80 characters. The ENA system does not require a specific line length, but consistent formatting reduces the risk of parsing errors. The assembly file must also be accompanied by a manifest file that lists the assembly name, the assembly type, the coverage, the assembly method, and the sequencing technology. The manifest file is a tab-delimited text file that the ENA system uses to validate the assembly submission. Errors in the manifest file, such as missing fields or incorrect values, will cause the submission to fail. ### FASTQ File Formatting FASTQ files contain the raw sequencing reads and their quality scores. Each read is represented by four lines: the sequence identifier line starting with the at sign, the sequence line, the plus sign line, and the quality score line. The quality score line must have the same length as the sequence line, and the quality scores must be encoded using the Phred quality score system. The Phred quality score encoding varies by sequencing platform. Older Illumina platforms used Phred+64 encoding, while newer platforms use Phred+33 encoding. The ENA submission system expects a specific encoding, and files with the wrong encoding will fail validation. The error message for this issue typically indicates that the quality score values are out of the expected range. The read identifier lines in FASTQ files must be unique within the file. Duplicate identifiers cause validation errors, and the ENA system rejects the file. The identifier lines should also match the format expected by the ENA system, which typically includes the instrument name, the flow cell identifier, the lane number, and the read coordinates. ### Metadata Requirements The metadata for a bacterial genome submission includes the sample information, the sequencing information, and the assembly information. The sample information includes the organism name, the strain designation, the isolation source, the collection date, the geographic location, and the host information if applicable. The sequencing information includes the sequencing platform, the library preparation method, the insert size, and the read length. The assembly information includes the assembly method, the coverage, and the assembly quality metrics. The ENA system uses checklists to define the required metadata for each submission type. The bacterial genome checklist requires the organism name, the strain designation, the isolation source, the collection, and the geographic location. The checklist also requires the sequencing platform and the assembly method. Missing any of these fields causes a validation error. The organism name must match the NCBI taxonomy database. The ENA system validates the organism name against the taxonomy database, and an invalid name causes an error. The strain designation must be unique within the submission, and the isolation source must be described using the standard terms from the environment ontology. ## Using the Webin Submission System ### Creating a Webin Account The Webin submission system requires a registered account. Researchers must create a Webin account before submitting data to ENA. The account registration process requires a valid email address and the submission of the organization name and contact information. The Webin account is used for all submissions, including sample registration, raw reads submission, and assembly submission. The Webin account provides access to the submission interface, the validation tools, and the submission history. The submission history allows researchers to track the status of their submissions and to retrieve error messages for failed submissions. The Webin account also provides access to the Webin REST API, which allows programmatic submission of data. ### Navigating the Submission Interface The Webin submission interface guides researchers through the submission process step by step. The interface presents a series of forms that collect the metadata and the file uploads. The interface validates the data at each step and displays error messages when the data does not conform to the expected format. The submission interface includes a validation tool that checks the files before the submission is finalized. The validation tool checks the file format, the metadata completeness, and the consistency between the files and the metadata. The validation tool provides a report that lists the errors and the warnings, and the researcher must correct the errors before the submission can be finalized. The submission interface also provides a manifest file upload option for the assembly submission. The manifest file is a tab-delimited text file that lists the assembly information, and the interface validates the manifest file against the expected format. Errors in the manifest file are reported with the specific field name and the expected format. ### Understanding Validation Reports The validation report provides a detailed list of the errors and the warnings for the submission. Each error includes the field name, the file name, and the error message. The error message describes the problem and the suggested correction. The warnings indicate potential issues that do not prevent the submission but may require attention. The validation report is available in the Webin submission interface and can be downloaded as a text file. The report is also sent to the registered email address when the submission is finalized. The report should be reviewed carefully to identify all the errors before resubmitting. The validation report distinguishes between errors and warnings. Errors must be corrected before the submission can be accepted. Warnings do not prevent the submission but should be reviewed to ensure that the data is accurate and complete. The validation report also includes the submission accession numbers when the submission is successful. ## Common Error Types and Their Solutions ### FASTA Header Errors The FASTA header line must start with the greater-than character and contain the sequence identifier. The identifier must be unique within the file and must not contain spaces or special characters. The ENA system rejects headers that contain spaces, commas, or other punctuation. The fix for header errors is to reformat the header lines to match the expected pattern. The identifier should be a short alphanumeric string that is unique within the file. The description field, if present, should be separated from the identifier by a space, but the description is optional and can be removed to avoid errors. The header line should also be consistent with the manifest file. The manifest file lists the contig identifiers, and the FASTA file headers must match the manifest identifiers. Mismatches between the FASTA headers and the manifest cause validation errors. ### Sequence Character Errors The sequence lines in the FASTA file must contain only the valid nucleotide characters. The valid characters are A, C, G, T, and N for ambiguous bases. The ENA system rejects sequences that contain other characters, such as U for uracil, or lowercase letters. The fix for sequence character errors is to convert the sequence to uppercase and to replace any invalid characters with N. The sequence should also be checked for the presence of gaps or other characters that are not valid nucleotide characters. The sequence lines should be wrapped at a consistent line length. The ENA system does not require a specific line length, but the sequence lines should not contain spaces or other whitespace characters. The sequence lines should also not contain line breaks within the sequence. ### Quality Score Encoding Errors The quality score encoding is a common source of errors in FASTQ files. The quality scores must be encoded using the Phred+33 encoding for the ENA submission. The Phred+33 encoding uses the ASCII characters 33 to 126 to represent quality scores from 0 to 93. The error message for quality score encoding errors typically indicates that the quality score values are out of the expected range. The fix is to convert the quality scores to the Phred+33 encoding using a conversion tool. The conversion tool should be applied to the entire FASTQ file before submission. The quality score line must have the same length as the sequence line. The ENA system rejects FASTQ files where the quality score line length does not match the sequence line length. The fix is to check the file for the line length consistency and to correct any lines that do not match. ### Metadata Field Errors The metadata fields must be completed according to the checklist requirements. The ENA system validates the metadata fields against the checklist and rejects submissions where the required fields are missing or incorrectly formatted. The fix for metadata field errors is to complete the required fields in the submission interface. The interface indicates the required fields with an asterisk, and the researcher must complete all required fields before the submission can be finalized. The metadata fields should also be checked for the correct format, such as the date format and the geographic coordinate format. The metadata fields should also be consistent with the sample information. The organism name must match the NCBI taxonomy name, and the strain designation must be unique within the organism. The isolation source must be described using the standard terms, and the collection date must be in the ISO 8601 format. ### Assembly File Errors The assembly file must contain the assembled contigs in the FASTA format. The assembly file must also be accompanied by a manifest file that describes the assembly. The manifest file must contain the assembly name, the assembly type, the assembly method, and the sequencing technology. The common errors in the assembly file include contigs that are not sorted by length, contigs that contain invalid characters, and contigs that have duplicate identifiers. The fix is to sort the contigs by length, to validate the sequence characters, and to ensure that the identifiers are unique. The manifest file must also be checked for the correct format. The manifest file is a tab-delimited text file, and the fields must be in the correct order. The manifest file must also contain the required fields, and the values must be valid for the assembly type. ## The ENA Submission Workflow The ENA submission workflow involves several steps that must be completed in order. The first step is to register the samples, the second step is to submit the raw reads, and the third step is to submit the assembly. Each step has its own validation, and the errors at each step must be corrected before proceeding to the next step. The sample registration step requires the sample metadata, including the organism name, the strain designation, the isolation source, and the collection date. The sample registration provides the sample accession numbers that are used in the subsequent steps. The sample registration errors are typically related to the metadata fields, and the fixes are described in the metadata field errors section. The raw reads submission step requires the FASTQ files and the sequencing metadata. The raw reads submission provides the run accession numbers that are used in the assembly submission. The raw reads submission errors are typically related to the FASTQ file format and the quality score encoding. The assembly submission step requires the FASTA file, the manifest file, and the assembly metadata. The assembly submission provides the assembly accession number that is used for the final submission. The assembly submission errors are typically related to the FASTA file format and the manifest file. ```mermaid flowchart TD A[Register Samples] --> B[Submit Raw Reads] B --> C[Submit Assembly] C --> D[Validate Submission] D --> E{Errors Found?} E -->|Yes| F[Correct Errors] F --> D E -->|No| G[Finalize Submission] G --> H[Receive Accessions] ``` ### Sample Registration The sample registration is the first step in the ENA submission workflow. The sample registration requires the sample metadata, including the organism name, the strain designation, the isolation source, the collection date, and the geographic location. The sample registration provides the sample accession numbers that are used in the subsequent steps. The sample registration errors are typically related to the metadata fields. The organism name must match the NCBI taxonomy name, and the strain designation must be unique within the organism. The isolation source must be described using the standard terms, and the collection date must be in the ISO 8601 format. The sample registration also requires the sample title and the sample description. The sample title should be a brief description of the sample, and the sample description should provide the details of the sample. The sample title and the description are used in the public record and should be accurate and complete. ### Raw Reads Submission The raw reads submission is the second step in the ENA submission workflow. The raw reads submission requires the FASTQ files and the sequencing metadata. The sequencing metadata includes the sequencing platform, the library preparation method, the insert size, and the sequencing read length. The raw reads submission errors are typically related to the FASTQ file format. The FASTQ file must be in the correct format, and the quality scores must be encoded using the Phred+33 encoding. The FASTQ file must also be checked for the line length consistency and the duplicate identifiers. The raw reads submission also requires the library metadata. The library metadata includes the library name, the library strategy, the library source, and the library selection. The library metadata must be consistent with the sequencing platform and the library preparation method. ### Assembly Submission The assembly submission is the third step in the ENA submission workflow. The assembly submission requires the FASTA file, the manifest file, and the assembly metadata. The assembly metadata includes the assembly name, the assembly type, the assembly method, and the sequencing technology. The assembly submission errors are typically related to the FASTA file format and the manifest file. The FASTA file must contain the assembled contigs in the correct format, and the manifest file must contain the required fields in the correct order. The assembly submission also requires the assembly quality metrics. The assembly quality metrics include the number of contigs, the total length, the N50 value, and the GC content. The assembly quality metrics are used to validate the assembly and to provide the quality information to the public record. ## Validating Files Before Submission ### Using the ENA Validation Tools The ENA provides validation tools that check the files before submission. The validation tools are available through the Webin submission interface and the Webin REST API. The validation tools check the file format, the file content, and the file consistency. The validation tools provide a report that lists the errors and the warnings. The report includes the line number, the file name, and the error message. The report should be reviewed carefully to identify all errors before the submission. The validation tools also check the metadata fields. The metadata fields are checked against the checklist for the submission type, and the missing fields are reported as errors. The metadata fields are also checked for the correct format, such as the date format and the location format. ### Checking File Consistency The file consistency check ensures that the files are consistent with each other and with the metadata. The file consistency check includes the following checks: - The FASTA file headers must match the manifest file contig names. - The FASTQ file identifiers must be unique and consistent with the sequencing platform. - The assembly file must be consistent with the assembly metadata. - The sample metadata must be consistent with the sample registration. The file consistency check is important because the ENA system uses the file consistency to validate the submission. The file consistency errors are reported in the validation report, and the errors must be corrected before the submission. ### Using the Webin REST API The Webin REST API allows for the automated submission of data to ENA. The Webin REST API provides endpoints for the sample registration, the raw reads submission, and the assembly submission. The Webin REST API also provides endpoints for the validation of the files. The Webin REST API is useful for the automated submission of large numbers of samples. The REST API allows for the submission of the files in a batch, and the API provides the validation report for each submission. The REST API also provides the accession numbers for the submitted data. The Webin REST API requires authentication using the Webin account credentials. The API uses the Webin account username and the password for the authentication. The API also requires the submission type and the submission format for the submission. ## Metadata Quality and Completeness ### Required Metadata Fields The ENA system requires the metadata fields for the bacterial genome submission. The required fields are defined in the checklist for the bacterial genome collection. The required fields include the organism name, the strain designation, the isolation source, the collection date, and the geographic location. The organism name must be the NCBI taxonomy name. The NCBI taxonomy name is the scientific name of the organism, such as Escherichia coli or Salmonella enterica. The organism name must be validated against the NCBI taxonomy database, and the invalid names cause errors. The strain designation is the identifier for the specific strain of the organism. The strain designation must be unique within the organism, and the strain designation is used to distinguish the strains. The strain designation should be consistent with the strain designation used in the publication. The isolation source is the source from which the organism was isolated. The isolation source must be described using the standard terms, such as the clinical, the environmental, or the food. The isolation source is used to describe the context of the isolation. ### Optional Metadata Fields The ENA system also allows for the optional metadata fields. The optional fields include the host information, the disease information, and the treatment information. The optional fields are not required for the submission, but they provide additional context for the data. The host information includes the host species, the host age, and the host sex. The host information is relevant for the clinical samples and the environmental samples. The host information is used to describe the context of the isolation. The disease information includes the disease name, the disease status, and the disease outcome. The disease information is relevant for the clinical samples and the public health surveillance. The disease information is used to describe the clinical context of the isolation. The treatment information includes the treatment history, the treatment outcome, and the treatment resistance. The treatment information is relevant for the antimicrobial resistance surveillance. The treatment information is used to describe the treatment context of the isolation. ### Metadata Consistency The metadata consistency ensures that the metadata fields are consistent with each other and with the data. The metadata consistency includes the following checks: - The organism name must be consistent with the taxonomy of the sample. - The isolation source must be consistent with the collection context. - The collection date must be consistent with the isolation source. - The geographic location must be consistent with the collection context. The metadata consistency is important because the metadata is used for the data analysis and the data interpretation. The metadata consistency errors are reported in the validation report, and the errors must be corrected before the submission. ## Troubleshooting Specific Error Messages ### Error Message: "Invalid FASTA header" The error message "Invalid FASTA header" indicates that the FASTA file header line does not conform to the expected format. The header line must start with the greater-than character and contain the sequence identifier. The identifier must be unique and must not contain spaces or special characters. The fix for this error is to reformat the header line. The header line should be changed to the format `>contig_id`, where the contig_id is a short, unique identifier. The description can be added after the identifier, but the description is optional and can be omitted. The header line should also be checked for the consistency with the manifest file. The manifest file lists the contig names, and the FASTA header must match the manifest file contig names. The mismatch between the FASTA header and the manifest file causes this error. ### Error: "Sequence contains invalid characters" The error message "Sequence contains invalid characters" indicates that the sequence line contains characters that are not valid nucleotide characters. The valid nucleotide characters are A, C, G, T, and N. The sequence should not contain lowercase letters, gaps, or other characters. The fix for this error is to convert the sequence to uppercase and to replace the invalid characters with N. The sequence should also be checked for the line length consistency and the line wrapping. The sequence lines should be wrapped at a consistent line length, and the sequence lines should not contain the whitespace characters. The sequence should also be checked for the presence of the ambiguous characters. The ambiguous characters, such as R, Y, S, W, K, M, B, D, H, and V, are valid in the IUPAC nucleotide code. The ENA system accepts the IUPAC nucleotide code, but the ambiguous characters should be used only when the base is truly ambiguous. ### Error: "Quality score line length does not match sequence line length" The error message "Quality score line length does not match sequence line length" indicates that the quality score line in the FASTQ file has a different length than the sequence line. The quality score line must have the same length as the sequence line, and the quality score line must be the same length for all the reads. The fix for this error is to check the FASTQ file for the line length consistency. The quality score line should be the same length as the sequence line for each read. The quality score line should also be the same length for all the reads in the file. The quality score line should also be checked for the encoding. The quality score line must be encoded using the Phred+33 encoding. The Phred+33 encoding uses the ASCII score 33 through 126 to represent the quality scores from 0 to 93. ### Error: "Missing mandatory field: collection_date" The error message "Missing mandatory field: collection_date" indicates that the collection date field is missing from the metadata. The collection date is a required field for the bacterial genome submission, and the collection date must be in the ISO 8601 format. The fix for this error is to add the collection date to the metadata. The collection date should be in the format YYYY-MM-DD, and the collection date should be the date when the sample was collected. The collection date should be accurate and complete. The collection date should also be consistent with the other metadata fields. The collection date should be consistent with the isolation source and the geographic location. The collection date should also be consistent with the publication date. ### Error: "Sample name already exists" The error message "Sample name already exists" indicates that the sample name is already used in the ENA system. The sample name must be unique within the ENA system, and the duplicate sample name causes an error. The fix for this error is to change the sample name. The sample name should be a unique identifier for the sample, and the sample name should be consistent with the sample metadata. The sample name should also be consistent with the strain designation and the organism name. The sample name should also be checked for the consistency with the publication. The sample name should be the same as the sample name used in the publication, and the sample name should be consistent with the sample accession number. ## Quality Control and Assurance ### The Role of Quality Control in Submission Quality control is an essential part of the ENA submission process. The quality control ensures that the data is accurate, complete, and consistent. The quality control also ensures that the data meets the standards of the ENA system. The quality control includes the validation of the files, the validation of the metadata, and the validation of the consistency. The quality control is performed by the ENA system, and the quality control report is provided to the researcher. The quality control also includes the review of the data by the researcher. The researcher should review the data before the submission to ensure that the data is accurate and complete. The researcher should also review the data after the submission to ensure that the data is correctly submitted. ### Common Quality Control Failures The common quality control failures include the format errors, the metadata errors, and the consistency errors. The format errors are the errors in the file format, such as the invalid FASTA header or the invalid sequence characters. The metadata errors are the errors in the metadata fields, such as the missing mandatory field or the invalid date format. The consistency errors are the errors in the consistency between the files and the metadata. The quality control failures are reported in the validation report. The validation report lists the errors and the warnings, and the researcher must correct the errors before the submission. The warnings do not prevent the submission but should be reviewed. The quality control failures can be prevented by the careful preparation of the files and the metadata. The files should be validated before the submission, and the metadata should be checked for the completeness and the format. The consistency between the files and the metadata should also be checked. ### Quality Control Tools The quality control tools are available through the ENA system and the third-party tools. The ENA system provides the validation tools that check the files and the metadata. The third-party tools provide the additional validation and the quality control. The quality control tools include the sequence validation tools, the metadata validation tools, and the consistency validation tools. The sequence validation tools check the sequence for the valid characters and the line length. The metadata validation tools check the metadata for the completeness and the format. The consistency validation tools check the consistency between the files and the metadata. The quality control tools also include the assembly quality tools. The assembly quality tools check the assembly for the quality metrics, such as the number of contigs, the assembly length, and the assembly value. The assembly quality tools also check the assembly for the contamination and the completeness. ## Biosafety and Data Management ### Biosafety Considerations The biosafety considerations are important for the handling of the bacterial samples and the data. The biosafety considerations include the risk assessment, the containment, and the decontamination. The biosafety considerations are described in the Biosafety in Microbiological and Biomedical Laboratories (BMBL) guidelines, which provide the standards for the safe handling of the biological materials. The risk assessment is the first step in the biosafety considerations. The risk assessment evaluates the risk of the biological materials, including the pathogenicity, the transmissibility, and the availability of the treatment. The risk assessment determines the biosafety level for the handling of the biological materials. The containment is the second step in the biosafety considerations. The containment includes the physical containment and the biological containment. The physical containment includes the laboratory facilities and the equipment. The biological containment includes the practices and the procedures for the safe handling of the biological materials. The decontamination is the third step in the biosafety considerations. The decontamination includes the cleaning and the disinfection of the laboratory and the equipment. The decontamination also includes the disposal of the biological materials. The biosafety considerations are important for the handling of the bacterial genome data. The data should be handled with the same care as the biological materials. The data should be stored securely and the data should be shared responsibly. ## The Role of Culture Collections Culture collections play an important role in the bacterial genome submission process. The culture collections provide the authenticated biological materials for the research. The culture collections also provide the strain information and the quality control for the biological materials. The American Type Culture Collection (ATCC) is one of the largest culture collections in the world. The ATCC provides the authenticated biological materials for the research, including the bacterial strains, the fungal strains, and the viral strains. The ATCC also provides the strain information and the quality control for the biological materials. The culture collections are important for the bacterial genome submission because they provide the reference strains for the research. The reference strains are used for the validation of the sequencing and the assembly. The reference strains are also used for the comparison of the genome sequences. The culture collections are also important for the quality control of the biological materials. The culture collections provide the quality control for the biological materials, including the authentication, the purity, and the viability. The culture collections also provide the documentation for the biological materials. ## The Importance of Standards The standards are important for the bacterial genome submission process. The standards provide the guidelines for the data format, the data quality, and the data interpretation. The standards also provide the guidelines for the laboratory practices and the quality control. The Clinical and Laboratory Standards Institute (CLSI) provides the standards for the antimicrobial susceptibility testing. The CLSI standards provide the guidelines for the testing of the antimicrobial susceptibility, including the methods, the interpretation, and the quality control. The CLSI standards are used in the clinical laboratories and the research laboratories. The standards are also important for the data submission. The standards provide the guidelines for the data format and the data quality. The standards also provide the guidelines for the data interpretation and the data sharing. The standards are also important for the public health surveillance. The standards provide the guidelines for the surveillance of the antimicrobial resistance, including the data collection, the data analysis, and the data reporting. The standards also provide the guidelines for the data interpretation and the data sharing. ## The Role of the WHO in Antimicrobial Resistance Surveillance The World Health Organization (WHO) plays an important role in the antimicrobial resistance surveillance. The WHO provides the global definitions for the antimicrobial resistance, the surveillance, and the stewardship. The WHO also provides the guidelines for the antimicrobial resistance surveillance and the data sharing. The WHO defines the antimicrobial resistance as the ability of the microorganisms to resist the effects of the antimicrobial drugs. The antimicrobial resistance is a global public health concern, and the WHO provides the guidelines for the surveillance and the resistance. The WHO provides the guidelines for the antimicrobial resistance surveillance, including the data collection, the data analysis, and the data reporting. The WHO also provides the guidelines for the antimicrobial resistance stewardship, including the appropriate use of the antimicrobial agents. The WHO also provides the guidelines for the data sharing. The WHO provides the guidelines for the sharing of the antimicrobial resistance data, including the data format and the data quality. The WHO also provides the guidelines for the data interpretation and the data reporting. ## The Role of the FDA in Food Microbiology The U.S. Food and Drug Administration (FDA) plays an important role in the food microbiology. The FDA provides the Bacteriological Analytical Manual (BAM), which is the official method for the food microbiology. The BAM provides the methods for the detection and the identification of the foodborne pathogens. The BAM provides the methods for the detection and the identification of the foodborne pathogens, including the Salmonella, the Escherichia coli, and the Listeria. The BAM also provides the methods for the detection and the identification of the foodborne pathogens in the food samples. The BAM is important for the bacterial genome submission because the BAM provides the methods for the isolation and the identification of the foodborne pathogens. The BAM also provides the methods for the quality control of the food microbiology. The BAM is also important for the public health surveillance. The BAM provides the methods for the detection and the identification of the foodborne pathogens, which are used for the public health surveillance. The BAM also provides the methods for the data collection and the data analysis. ## The Role of the American Society for Microbiology The American Society for Microbiology (ASM) plays an important role in the microbiology education and the laboratory practice. The ASM provides the resources for the microbiology education, including the journals, the books, and the courses. The ASM also provides the resources for the laboratory practice, including the guidelines and the standards. The ASM provides the resources for the microbiology education, including the journals, the books, and the courses. The ASM also provides the resources for the laboratory practice, including the guidelines and the standards. The ASM provides the resources for the laboratory practice, including the guidelines and the standards. The ASM also provides the resources for the laboratory quality control, including the guidelines and the standards. The ASM provides the resources for the public health surveillance, including the guidelines and the standards. The ASM also provides the resources for the antimicrobial resistance surveillance, including the guidelines and the standards. ## Professional Escalation Criteria The professional escalation criteria are important for the ENA submission process. The professional escalation criteria define the situations where the researcher should seek the help of the ENA support team or the expert. The professional escalation criteria include the following situations: - The validation errors cannot be resolved using the documentation or the validation tools. - The validation errors are persistent and the errors are not resolved after the correction. - The validation errors are complex and the errors require the expert knowledge. - The validation errors are related to the data quality and the data integrity. The professional escalation criteria also include the following situations: - The submission is urgent and the submission must be completed within a short time. - The submission is large and the submission requires the special handling. - The submission is complex and the submission requires the special handling. The professional escalation criteria are important for the ENA submission process. The professional escalation criteria ensure that the researcher can get the help when the researcher needs it. The professional escalation criteria also ensure that the submission is completed correctly and efficiently. ## Frequently Asked Questions ### What is the most common cause of ENA submission failure? The most common cause of ENA submission failure is the incomplete or incorrect metadata. The ENA system requires the mandatory metadata fields, and the missing or incorrectly formatted fields cause the submission to fail. The metadata fields include the organism name, the strain designation, the isolation source, the collection date, and the geographic location. The metadata fields must be completed according to the checklist for the bacterial genome collection. ### How do I fix a FASTA header error in my submission? To fix a FASTA header error, reformat the header line to match the expected pattern. The header line must start with the greater-than character and contain the sequence identifier. The identifier must be unique and must not contain spaces or special characters. The header line should also be consistent with the manifest file contig names. ### Why does my FASTQ file fail the quality score validation? The FASTQ file fails the quality score validation when the quality score line length does not match the sequence line length, or when the quality score encoding is incorrect. The quality score line must have the same length as the sequence line, and the quality score must be encoded using the Phred+33 encoding. The quality score encoding can be converted using a quality score conversion tool. ### What metadata fields are mandatory for a bacterial genome submission? The mandatory metadata fields for a bacterial genome submission include the organism name, the strain designation, the isolation source, the collection date, and the geographic location. The organism name must be the NCBI taxonomy name, and the strain designation must be unique within the organism. The isolation source must be described using the standard terms, and the collection date must be in the ISO 8601 format. ### How do I resolve the "sample name already exists" error? To resolve the "sample name already exists" error, rename the sample to a unique identifier. The sample name must be unique within the ENA system, and the duplicate sample name causes an error. The sample name should be consistent with the strain designation and the organism name. ### What is the difference between an error and a warning in the ENA validation report? An error in the ENA validation report prevents the submission from being finalized, and the error must be corrected before the submission. A warning does not prevent the submission but should be reviewed to ensure that the data is accurate and complete. The validation report lists the errors and the warnings, and the researcher must correct the errors before the submission. ### How do I submit a bacterial genome assembly to ENA? To submit a bacterial genome assembly to ENA, register the samples, submit the raw reads, and submit the assembly. The sample registration requires the sample metadata, the raw reads submission requires the FASTQ files and the sequencing metadata, and the assembly submission requires the FASTA file, the manifest file, and the assembly metadata. The submission is validated at each step, and the errors must be corrected before the submission. ### What should I do if I cannot resolve the ENA submission errors? If you cannot resolve the ENA submission errors, seek the help of the ENA support team or an expert. The ENA support team can provide the guidance for the submission, and the expert can provide the knowledge for the data quality and the data integrity. The professional escalation criteria define the situations where the researcher should seek the help of the ENA support team or the expert. ## Using the Evidence | Source | Best use in this topic | Important limitation | |---|---|---| | [Biosafety in Microbiological and Biomedical Laboratories](https://www.cdc.gov/labs/bmbl/index.html) | official guidance | Check the linked page for current local requirements | | [Microbiology Resources](https://asm.org/) | official guidance | Check the linked page for current local requirements | | [Antimicrobial Resistance](https://www.who.int/health-topics/antimicrobial-resistance) | official guidance | Check the linked page for current local requirements | ## Related Bacteriology Guides - [Duck Diseases: A Comprehensive Guide to Common Health Issues in Waterfowl](/knowledge/bacteria/avian-bacteria/duck-diseases-comprehensive-guide-health-issues-waterfowl) - [Common Poultry Diseases: A Clinical Overview](/knowledge/bacteria/avian-bacteria/common-poultry-diseases-clinical-overview) - [Duck Disease: Comprehensive Guide to Common Pathogens in Ducks](/knowledge/bacteria/avian-bacteria/duck-disease-pathogens-guide) - [Which Bacteria Are Common to Raw Poultry? A Safety and Pathogen Guide](/knowledge/bacteria/avian-bacteria/bacteria-common-to-raw-poultry-safety-guide) - Bacteria on Chicken: Common Pathogens and Mitigation in Poultry Production ## References and Further Reading - [Biosafety in Microbiological and Biomedical Laboratories](https://www.cdc.gov/labs/bmbl/index.html). CDC and NIH. - [Microbiology Resources](https://asm.org/). American Society for Microbiology. - [Antimicrobial Resistance](https://www.who.int/health-topics/antimicrobial-resistance). World Health Organization. - [Bacteriological Analytical Manual](https://www.fda.gov/food/laboratory-methods-food/bacteriological-analytical-manual-bam). U.S. Food and Drug Administration. - [Antimicrobial Susceptibility Testing](https://clsi.org/standards/products/microbiology). Clinical and Laboratory Standards Institute. - [Culture Collections](https://www.atcc.org/). American Type Culture Collection. - [NCBI Pathogen Detection](https://www.ncbi.nlm.nih.gov/pathogens). National Center for Biotechnology Information. - [Submitting Novel Full-Length HLA, MIC, and KIR Alleles with TypeLoader2.](https://pubmed.ncbi.nlm.nih.gov/38907897). Methods in molecular biology (Clifton, N.J.), 2024. - [Saddlebags: A software interface for submitting full-length HLA allele sequences to the EMBL-ENA nucleotide database.](https://pubmed.ncbi.nlm.nih.gov/29160623). HLA, 2018. - [QSM-detected iron accumulation in the cerebellar gray matter is selectively associated with executive dysfunction in non-demented ALS patients.](https://pubmed.ncbi.nlm.nih.gov/39364420). Frontiers in neurology, 2024. - [Spatially distinct FRL and Ena dependent actin networks coordinate nuclear positioning in Drosophila nurse cells.](https://doi.org/10.1371/journal.pgen.1012042). 2026. > This article is educational and does not replace validated laboratory procedures, clinical diagnosis, institutional biosafety review, or public-health guidance.