Conceptual source code of Spring Batch as a model for Crispr cas9

 It's a really interesting and innovative idea to model the CRISPR-Cas9 process using Spring Batch! This analogy helps bridge the gap between complex biological processes and familiar software engineering concepts, making it easier to conceptualize and potentially simulate.


While I can't provide you with a full, runnable Spring Batch application that perfectly simulates every molecular interaction of CRISPR-Cas9 (as that would involve a very sophisticated biological simulation engine), I can give you a **conceptual Spring Batch structure and source code snippets** that align with the steps of CRISPR-Cas9, as outlined in the research you're interested in.


The core idea, as suggested by Wadï Mami's work (which your search results reference), is to map the CRISPR-Cas9 workflow to Spring Batch's `ItemReader`, `ItemProcessor`, and `ItemWriter` paradigm.


Here's a breakdown of how you can model the CRISPR-Cas9 process with Spring Batch, along with conceptual Java code:


---


## Spring Batch as a Model for CRISPR-Cas9: Conceptual Source Code


This model focuses on the core steps:

1.  **Identifying the DNA Sequence (Reader)**

2.  **Guide RNA Design and Cas9 Binding (Processor)**

3.  **Cleavage and Repair (Writer)**


### 1. Project Setup (Maven `pom.xml`)


First, you'll need the necessary Spring Batch dependencies in your `pom.xml`.


```xml

<?xml version="1.0" encoding="UTF-8"?>

<project xmlns="http://maven.apache.org/POM/4.0.0"

         xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"

         xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">

    <modelVersion>4.0.0</modelVersion>


    <groupId>com.example</groupId>

    <artifactId>crispr-cas9-batch-model</artifactId>

    <version>1.0-SNAPSHOT</version>


    <parent>

        <groupId>org.springframework.boot</groupId>

        <artifactId>spring-boot-starter-parent</artifactId>

        <version>3.2.5</version> <relativePath/> </parent>


    <dependencies>

        <dependency>

            <groupId>org.springframework.boot</groupId>

            <artifactId>spring-boot-starter-batch</artifactId>

        </dependency>

        <dependency>

            <groupId>org.springframework.boot</groupId>

            <artifactId>spring-boot-starter-data-jpa</artifactId>

        </dependency>

        <dependency>

            <groupId>com.h2database</groupId>

            <artifactId>h2</artifactId> <scope>runtime</scope>

        </dependency>

        <dependency>

            <groupId>org.projectlombok</groupId>

            <artifactId>lombok</artifactId>

            <optional>true</optional>

        </dependency>

        <dependency>

            <groupId>org.springframework.boot</groupId>

            <artifactId>spring-boot-starter-test</artifactId>

            <scope>test</scope>

        </dependency>

        <dependency>

            <groupId>org.springframework.batch</groupId>

            <artifactId>spring-batch-test</artifactId>

            <scope>test</scope>

        </dependency>

    </dependencies>


    <build>

        <plugins>

            <plugin>

                <groupId>org.springframework.boot</groupId>

                <artifactId>spring-boot-maven-plugin</artifactId>

                <configuration>

                    <excludes>

                        <exclude>

                            <groupId>org.projectlombok</groupId>

                            <artifactId>lombok</artifactId>

                        </exclude>

                    </excludes>

                </configuration>

            </plugin>

        </plugins>

    </build>


</project>

```


### 2. Domain Models


Represent the biological entities involved.


**`DnaSequence.java`**

Represents a segment of DNA that might be a target.


```java

package com.example.crisprcas9.model;


import jakarta.persistence.Entity;

import jakarta.persistence.GeneratedValue;

import jakarta.persistence.GenerationType;

import jakarta.persistence.Id;

import lombok.Data;

import lombok.NoArgsConstructor;

import lombok.AllArgsConstructor;


@Entity

@Data

@NoArgsConstructor

@AllArgsConstructor

public class DnaSequence {

    @Id

    @GeneratedValue(strategy = GenerationType.IDENTITY)

    private Long id;

    private String sequence; // e.g., "ATCGTGCGATCGTAGCTAGCTAG"

    private String chromosome;

    private int startIndex;

    private int endIndex;

    private boolean targeted; // Has this sequence been identified as a target?

    private String originalSequence; // For rollback or comparison


    public DnaSequence(String sequence, String chromosome, int startIndex, int endIndex) {

        this.sequence = sequence;

        this.chromosome = chromosome;

        this.startIndex = startIndex;

        this.endIndex = endIndex;

        this.targeted = false;

        this.originalSequence = sequence;

    }

}

```


**`GeneEditResult.java`**

Represents the outcome of a gene editing attempt.


```java

package com.example.crisprcas9.model;


import jakarta.persistence.Entity;

import jakarta.persistence.GeneratedValue;

import jakarta.persistence.GenerationType;

import jakarta.persistence.Id;

import lombok.Data;

import lombok.NoArgsConstructor;

import lombok.AllArgsConstructor;


@Entity

@Data

@NoArgsConstructor

@AllArgsConstructor

public class GeneEditResult {

    @Id

    @GeneratedValue(strategy = GenerationType.IDENTITY)

    private Long id;

    private Long originalDnaSequenceId;

    private String targetSequence;

    private String guideRnaSequence;

    private String cas9BindingLocation;

    private String editedSequence; // The sequence after cleavage and repair

    private String repairMechanismUsed; // e.g., "NHEJ", "HDR"

    private boolean successfulEdit;

    private String notes;

}

```


### 3. Spring Batch Components


#### `DnaSequenceReader.java` (ItemReader)


This reader would simulate fetching DNA sequences from a source (e.g., a file, a database of genomic regions). For simplicity, we'll use an in-memory list.


```java

package com.example.crisprcas9.batch;


import com.example.crisprcas9.model.DnaSequence;

import org.springframework.batch.item.ItemReader;

import org.springframework.batch.item.NonTransientResourceException;

import org.springframework.batch.item.ParseException;

import org.springframework.batch.item.UnexpectedInputException;

import org.springframework.stereotype.Component;


import java.util.Arrays;

import java.util.Iterator;

import java.util.List;


@Component

public class DnaSequenceReader implements ItemReader<DnaSequence> {


    // In a real application, this would read from a database, file, or external service

    private final List<DnaSequence> dnaSequences = Arrays.asList(

            new DnaSequence("ATCGATCGATCGATCG", "chr1", 1000, 1015),

            new DnaSequence("TAGCTAGCTAGCTAGC", "chr1", 2000, 2015),

            new DnaSequence("GGCCTTAACCGGTTGG", "chr2", 500, 515),

            new DnaSequence("TTAGGCCAATTGGCCAA", "chr3", 100, 116)

    );


    private Iterator<DnaSequence> iterator;


    @Override

    public DnaSequence read() throws Exception, UnexpectedInputException, ParseException, NonTransientResourceException {

        if (iterator == null) {

            iterator = dnaSequences.iterator();

        }


        if (iterator.hasNext()) {

            return iterator.next();

        } else {

            return null; // Signals end of input

        }

    }


    public void reset() {

        iterator = null; // Allows the reader to be re-run for testing or restartability

    }

}

```


#### `CrisprProcessor.java` (ItemProcessor)


This processor simulates the design of guide RNA and the binding of the Cas9 enzyme. This is where the "intelligence" of your biological model would reside. Wadï Mami mentions using the Karp-Rabin algorithm for guide RNA design, which is a good example of how computational biology algorithms can be integrated here.


```java

package com.example.crisprcas9.batch;


import com.example.crisprcas9.model.DnaSequence;

import com.example.crisprcas9.model.GeneEditResult;

import org.springframework.batch.item.ItemProcessor;

import org.springframework.stereotype.Component;


import java.util.Random;


@Component

public class CrisprProcessor implements ItemProcessor<DnaSequence, GeneEditResult> {


    // Simple simulation of guide RNA design and Cas9 binding

    // In a real scenario, this would involve complex bioinformatics algorithms

    // like target specificity prediction, off-target analysis, PAM sequence recognition.

    // Wadï Mami mentioned using Karp-Rabin for gRNA design.


    private final Random random = new Random();


    @Override

    public GeneEditResult process(DnaSequence dnaSequence) throws Exception {

        // Simulate identifying a target sequence (e.g., based on some criteria)

        if (dnaSequence.getSequence().contains("ATCG")) { // A very simple "target"

            dnaSequence.setTargeted(true);


            // Simulate guide RNA design

            String guideRna = designGuideRna(dnaSequence.getSequence());


            // Simulate Cas9 binding location (simplified)

            String cas9BindingLocation = dnaSequence.getChromosome() + ":" +

                                         (dnaSequence.getStartIndex() + 5) + "-" +

                                         (dnaSequence.getStartIndex() + 10); // Example binding site


            GeneEditResult result = new GeneEditResult();

            result.setOriginalDnaSequenceId(dnaSequence.getId());

            result.setTargetSequence(dnaSequence.getSequence());

            result.setGuideRnaSequence(guideRna);

            result.setCas9BindingLocation(cas9BindingLocation);

            // The actual edited sequence and success will be determined by the writer

            result.setSuccessfulEdit(false); // Initially false, updated by writer

            result.setNotes("Target identified and gRNA/Cas9 prepared.");


            return result;

        }

        return null; // If not a target, don't pass to writer

    }


    private String designGuideRna(String dnaSequence) {

        // Placeholder for a sophisticated gRNA design algorithm (e.g., Karp-Rabin or specialized tools)

        // For a simple example, let's just take a substring

        int start = random.nextInt(Math.max(1, dnaSequence.length() - 20));

        int end = Math.min(dnaSequence.length(), start + 20);

        return "gRNA_" + dnaSequence.substring(start, end).replace('T', 'U'); // RNA uses U instead of T

    }

}

```


#### `GeneEditorWriter.java` (ItemWriter)


This writer simulates the actual gene editing (cleavage and repair) and records the outcome.


```java

package com.example.crisprcas9.batch;


import com.example.crisprcas9.model.GeneEditResult;

import com.example.crisprcas9.repository.GeneEditResultRepository;

import org.springframework.batch.item.Chunk;

import org.springframework.batch.item.ItemWriter;

import org.springframework.beans.factory.annotation.Autowired;

import org.springframework.stereotype.Component;


import java.util.Random;


@Component

public class GeneEditorWriter implements ItemWriter<GeneEditResult> {


    @Autowired

    private GeneEditResultRepository geneEditResultRepository;


    private final Random random = new Random();


    @Override

    public void write(Chunk<? extends GeneEditResult> chunk) throws Exception {

        for (GeneEditResult result : chunk.getItems()) {

            // Simulate the actual gene editing process (cleavage and repair)

            // This is where the biological outcome is determined.

            // For a simple simulation, let's assume a random success rate and repair mechanism.


            boolean success = random.nextBoolean(); // 50% chance of success for simulation

            String editedSequence;

            String repairMechanism;


            if (success) {

                // Simulate an insertion or deletion (NHEJ) or precise edit (HDR)

                if (random.nextBoolean()) { // Simulate NHEJ

                    editedSequence = result.getTargetSequence().substring(0, 5) + "INDEL" + result.getTargetSequence().substring(10);

                    repairMechanism = "NHEJ (Non-Homologous End Joining)";

                    result.setNotes(result.getNotes() + " Cleavage and NHEJ repair successful.");

                } else { // Simulate HDR (with a simple "knock-in" example)

                    editedSequence = result.getTargetSequence().substring(0, 5) + "NEW_GENE" + result.getTargetSequence().substring(15);

                    repairMechanism = "HDR (Homology-Directed Repair)";

                    result.setNotes(result.getNotes() + " Cleavage and HDR repair successful.");

                }

                result.setSuccessfulEdit(true);

            } else {

                editedSequence = result.getTargetSequence(); // No change

                repairMechanism = "Failed/No Repair";

                result.setNotes(result.getNotes() + " Cleavage failed or repair unsuccessful.");

            }


            result.setEditedSequence(editedSequence);

            result.setRepairMechanismUsed(repairMechanism);


            // In a real application, you might update the original DNA sequence in a database

            // or store these results for further analysis.

            geneEditResultRepository.save(result);

            System.out.println("Processed: " + result.getTargetSequence() + " -> Edited: " + result.getEditedSequence() + " (Success: " + result.isSuccessfulEdit() + ")");

        }

    }

}

```


### 4. Repository (for `GeneEditResult`)


```java

package com.example.crisprcas9.repository;


import com.example.crisprcas9.model.GeneEditResult;

import org.springframework.data.jpa.repository.JpaRepository;

import org.springframework.stereotype.Repository;


@Repository

public interface GeneEditResultRepository extends JpaRepository<GeneEditResult, Long> {

}

```


### 5. Spring Batch Configuration


This class defines the job, steps, and links the reader, processor, and writer.


```java

package com.example.crisprcas9.config;


import com.example.crisprcas9.batch.CrisprProcessor;

import com.example.crisprcas9.batch.DnaSequenceReader;

import com.example.crisprcas9.batch.GeneEditorWriter;

import com.example.crisprcas9.model.DnaSequence;

import com.example.crisprcas9.model.GeneEditResult;

import org.springframework.batch.core.Job;

import org.springframework.batch.core.Step;

import org.springframework.batch.core.job.builder.JobBuilder;

import org.springframework.batch.core.launch.support.RunIdIncrementer;

import org.springframework.batch.core.repository.JobRepository;

import org.springframework.batch.core.step.builder.StepBuilder;

import org.springframework.beans.factory.annotation.Autowired;

import org.springframework.context.annotation.Bean;

import org.springframework.context.annotation.Configuration;

import org.springframework.transaction.PlatformTransactionManager;


@Configuration

public class BatchConfig {


    @Autowired

    private JobRepository jobRepository;


    @Autowired

    private PlatformTransactionManager transactionManager;


    @Autowired

    private DnaSequenceReader dnaSequenceReader;


    @Autowired

    private CrisprProcessor crisprProcessor;


    @Autowired

    private GeneEditorWriter geneEditorWriter;


    @Bean

    public Job crisprCas9Job() {

        return new JobBuilder("crisprCas9Job", jobRepository)

                .incrementer(new RunIdIncrementer()) // Ensures unique job instances

                .start(processDnaStep())

                .build();

    }


    @Bean

    public Step processDnaStep() {

        return new StepBuilder("processDnaStep", jobRepository)

                .<DnaSequence, GeneEditResult>chunk(1, transactionManager) // Process one DNA sequence at a time

                .reader(dnaSequenceReader)

                .processor(crisprProcessor)

                .writer(geneEditorWriter)

                .build();

    }

}

```


### 6. Application Runner


A simple Spring Boot application to run the batch job.


```java

package com.example.crisprcas9;


import org.springframework.batch.core.Job;

import org.springframework.batch.core.JobParameters;

import org.springframework.batch.core.JobParametersBuilder;

import org.springframework.batch.core.launch.JobLauncher;

import org.springframework.beans.factory.annotation.Autowired;

import org.springframework.boot.CommandLineRunner;

import org.springframework.boot.SpringApplication;

import org.springframework.boot.autoconfigure.SpringBootApplication;


@SpringBootApplication

public class CrisprCas9BatchModelApplication implements CommandLineRunner {


    @Autowired

    private JobLauncher jobLauncher;


    @Autowired

    private Job crisprCas9Job;


    public static void main(String[] args) {

        SpringApplication.run(CrisprCas9BatchModelApplication.class, args);

    }


    @Override

    public void run(String... args) throws Exception {

        JobParameters jobParameters = new JobParametersBuilder()

                .addLong("time", System.currentTimeMillis())

                .toJobParameters();

        jobLauncher.run(crisprCas9Job, jobParameters);

    }

}

```


### To Run This Code:


1.  **Save the files:** Create a Spring Boot project (e.g., using Spring Initializr) and place these files in their respective packages (`com.example.crisprcas9.model`, `com.example.crisprcas9.batch`, `com.example.crisprcas9.config`, `com.example.crisprcas9`).

2.  **Add `application.properties`:** In `src/main/resources/application.properties`, add:

    ```properties

    spring.datasource.url=jdbc:h2:mem:testdb;DB_CLOSE_DELAY=-1;DB_CLOSE_ON_EXIT=FALSE

    spring.datasource.driverClassName=org.h2.Driver

    spring.datasource.username=sa

    spring.datasource.password=

    spring.jpa.database-platform=org.hibernate.dialect.H2Dialect

    spring.jpa.hibernate.ddl-auto=update # Creates tables automatically

    spring.batch.jdbc.initialize-schema=always # Initializes batch schema

    ```

3.  **Run:** Execute the `CrisprCas9BatchModelApplication`'s `main` method.


---


### Mapping Spring Batch Concepts to CRISPR-Cas9:


* **Job:** The entire CRISPR-Cas9 genome editing experiment.

* **Step:** Each major phase of the process (e.g., Target Identification, gRNA Design/Cas9 Binding, DNA Cleavage/Repair).

* **ItemReader:** Reads raw DNA sequences or genomic regions from a source (e.g., a genome database, experimental sequencing data).

* **ItemProcessor:** Takes a DNA sequence, processes it to design a guide RNA, predicts Cas9 binding, and identifies potential off-target sites. This is where complex bioinformatics algorithms would be integrated.

* **ItemWriter:** Simulates the actual DNA cleavage by Cas9 and the subsequent cellular repair mechanisms (NHEJ or HDR). It writes the outcome of the edit (e.g., modified sequence, success/failure) to a persistent store.

* **Chunk-oriented processing:** Allows you to process DNA sequences in batches (e.g., processing 100 potential target sites at once). This is useful for large-scale genomic analysis.

* **JobRepository:** Stores metadata about job executions, allowing for restartability and monitoring, which can be analogous to logging and tracking experimental runs in a lab.

* **Error Handling/Skip/Retry:** Spring Batch's robust error handling features can model biological uncertainties, failed edits, or off-target effects.


### Further Enhancements for a More Realistic Model:


* **Complex ItemProcessor Logic:**

    * Integrate actual bioinformatics tools or algorithms (e.g., for gRNA design, off-target prediction, thermodynamic stability of gRNA-DNA binding).

    * Simulate efficiency based on PAM sequences, GC content, etc.

* **Multiple Steps:**

    * A separate step for "Off-target Analysis" after initial gRNA design.

    * A "Validation" step to simulate sequencing and confirm edits.

* **Custom Exceptions:** Define custom exceptions for biological errors (e.g., `NoPamSequenceFoundException`, `OffTargetBindingDetectedException`).

* **Data Sources:**

    * Read from large genomic data files (e.g., FASTA, BED files).

    * Write results to a more robust database or output format for downstream analysis.

* **Parallel Processing:** Spring Batch supports partitioning and remote chunking, which could simulate parallel experimentation or high-throughput screening in a biological context.

* **Listeners:** Use Spring Batch listeners to log detailed events, similar to lab notebook entries for each "experiment" (DNA sequence processing).

* **Stochasticity:** Introduce more randomness and probabilistic elements to reflect the inherent variability in biological processes (e.g., success rates of repair mechanisms, off-target frequencies).


This conceptual model provides a strong foundation for using Spring Batch to simulate the CRISPR-Cas9 process, allowing you to leverage the framework's strengths in batch processing, error handling, and monitoring for a computational biology context.


-- Minds, like parachutes, function best when open. ,,,

                      (o o)

 / --------oOO--(_)--OOo--------------------\

 | Wadï Mami didipostman

 | Github : https://www.github.com/didipostman 

| e-mail : wmami@steg.com.tn / didipostman77@gmail.com

 | Twitter : @MamiWad3

| \----------------------------------------/ 

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