Leandro Pio de Sousa^1,2, Ludmila dos Passos e Silva¹, Marcelo Mendes Brandão², Oliveiro Guerreiro Filho³

¹Laboratório de Interações Multitróficas e Biodiversidade, Departamento de Biologia Animal, Instituto de Biologia, Universidade Estadual de Campinas (UNICAMP),
Campinas, Brazil
²Center for Molecular Biology and Genetic Engineering (CBMEG), State University of Campinas (Unicamp), Campinas, São Paulo, 13083-875, Brazil
³Centro de Café Alcides Carvalho, Instituto Agronômico (IAC), Campinas, São Paulo, Brazil
^∗Corresponding author. E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Link permanente: https://url.bioinfoguy.net/fnaf133 

Coffee leaf mine, a small moth of the family Lyonetiidae, is considered one of the most important coffee pests. Despite its economic importance, almost nothing is known about its microbiome. Seeking to help fill this knowledge gap, in our study, we investigated the bacteriome of the insect (larvae and adults) and coffee leaves by sequencing the 16S rRNA gene. We found that at the phylum level  Pseudomonadota and Bacteroidota dominate. At the genus level, leaves were mainly dominated by Sphingomonas and Methylobacterium; the caterpillars were mainly dominated by Xanthomonas and Paracoccus; the adult moths were mainly dominated by Acinetobacter and Klebsiella. We estimate that the contribution to the bacteriome of adult moths comes from larvae, 50%, from leaves, 40%, and 10% from other sources. Several bacteria with the potential to degrade insecticides and secondary plant compounds were found, which leads to the expectation that they may help their hosts in resisting these toxic compounds. We hope that this work will contribute to encouraging further investigation of this important coffee pest.

Data availability

NCBI BioProject under the accession number PRJNA1004833

Kaira Cristina Peralis Tomaz¹, Felipe Ciamponi², Rafaela Pacheco¹, Jennifer Santos¹, Mariana Cavalheiro³, Fabio Patroni^1,4, Julio Vancini Bernardi^1,5, Murilo Meneghetti¹ , Lorena⁶, Alexandre Rossi Paschoal⁶, Marcelo Mendes Brandão^1*.

1 – Integrative and System Biology Laboratory (LaBIS); Universidade Estadual de Campinas (Unicamp), Campinas, Brazil; 2 – Suzano S.A. (FuturaGene—Biotech Division), Itapetininga, Brazil; 3 – Genomics for Climate Change Research Center, Universidade Estadual de Campinas, Campinas, SP, Brasil; 4 - Brazilian Centre for Research in Energy and Materials (CNPEM), Ministry for Science, Technology, and Innovations (MCTI), Campinas, Brazil; 5 - Laboratory of Enzymology and Molecular Biology of Microorganisms (LEBIMO), Universidade Estadual de Campinas, Campinas, SP, Brasil; 6 - Department of Computer Science, The Federal University of Technology – Paraná (UTFPR)The institution will open in a new tab, Cornélio Procópio, Brazil

* Correspondence author: This email address is being protected from spambots. You need JavaScript enabled to view it.

Background:
Polygenic diseases, such as Alzheimer's disease (AD) and type 2 diabetes mellitus (T2D), arise from the cumulative effect of numerous genetic variants and complex gene-environment interactions, presenting significant challenges for genetic analysis and clinical management. Both AD and T2D are increasing in prevalence globally and are hypothesized to share genetic risk factors, yet the underlying mechanisms remain poorly understood.

Methods:
This study developed an open-source bioinformatics pipeline to investigate shared genetic architecture (pleiotropy) between AD and T2D using whole-exome sequencing data from the dbGaP repository. Three alignment tools (Bowtie2, BWA-MEM, BWA-MEM2) and four variant callers (GATK, BCFtools, DeepVariant, FreeBayes) were benchmarked for computational efficiency and variant detection. Genome-wide association studies (GWAS) were performed for both diseases, followed by intersection analysis to identify pleiotropic single nucleotide polymorphisms (SNPs). Variants were annotated and filtered for clinical relevance and evolutionary conservation. Functional enrichment analyses were conducted using Gene Ontology (GO) clustering via REVIGO.

Results:
BWA-MEM2 and DeepVariant demonstrated optimal computational performance for alignment and variant calling, respectively. GWAS identified 1,264 nominally significant pleiotropic SNPs (p < 0.05 in both diseases), which were filtered to 89 high-confidence variants enriched for missense and intronic effects. Functional annotation revealed shared pathways involving carbohydrate metabolism, extracellular matrix organization, and steroid metabolism, supporting the hypothesis of common metabolic and neurovascular mechanisms underlying AD-T2D comorbidity. All scripts, datasets, and results are openly available to promote reproducibility and collaborative research.

Conclusions:
The open-source pipeline enables scalable, reproducible analysis of polygenic disease genetics and highlights shared biological processes between AD and T2D. This approach demonstrates the value of open science frameworks in accelerating discoveries and facilitating the development of targeted interventions for complex diseases. Limitations include potential ethnic bias and computational resource requirements, which future work may address through federated learning and expanded population datasets

 

Supplementary material

All supplementary material are available at https://doi.org/10.25824/redu/5MNXME,

Scripts availability

the pipeline scripts are present in https://github.com/labis-unicamp/pipeline1

Permanent link

https://url.bioinfoguy.net/pipeline1paper 

Marcelo Mendes Brandão¹
1 Universidade Estadual de Campinas (UNICAMP), Campinas, SP, Brazil
This email address is being protected from spambots. You need JavaScript enabled to view it.

This article examines the fundamental importance of functional annotation in contemporary scientific research within the context of increasingly affordable molecular sequencing technologies and improved information accessibility. I explore how functional annotation serves as the critical bridge between raw sequence data and meaningful biological insights, driving progress across multiple scientific disciplines and applications. The integration of comprehensive functional annotation approaches is revealed as essential for maximizing the value of expand-ing molecular datasets and accelerating scientific discovery in the post-genomic era. In this context I present DeNSAS (De Novo Sequence Annotation System), a comprehensive, reference-free pipeline designed for functional annotation of transcripts, proteins, and genes in genome assemblies that lack reference annotation. Developed in-house, this automated system integrates multiple public databases and computational tools to provide accurate functional characterization of sequences without requiring a reference genome.

 

Micael Siegert Schimmunech^a, Carolina Deuttner Neumann Barroso^a, Anderson Ferreira Da Cunha^b, Marcelo Mendes Brandão^c, Daniel Cruz^d , Karina Ishida^d, Marcelo Beltrão Molento^a,*
^a Laboratory of Veterinary Clinical Parasitology, Department of Veterinary Medicine, Federal University of Paraná, Curitiba, PR, Brazil. This email address is being protected from spambots. You need JavaScript enabled to view it. 
^b Laboratory of Biochemistry and Applied Genetics, Department of Genetics and Evolution, Federal University of São Carlos, São Carlos, Brazil.
^c Laboratory of Integrative and Systemic Biology, Center of Molecular Biology and Genetic Engineering, Universidade Estadual de Campinas, Campinas, São Paulo, Brazil.
^d World Animal Protection. São Paulo, SP, Brazil.

Pig farming has a significant environmental impact and generates substantial waste. Conventional wastewater treatment on farms often fails to eliminate pathogens, posing transmission risks. This study examined the microbiome of water samples (n=10) from pig farm environments (n=6) and urban areas (n=4) in Brazil. Pig farm samples were from Itambaracá, Paraná, and Chapecó, Santa Catarina, while urban samples were from Curitiba, Paraná, Joinville, and Santa Catarina. Samples included two from before (UP) and after (DOWN) pig farm presence, and two from a city river (CITY) near pig farms. Urban samples were taken from river sources (n=2) and near metropolitan perimeters (n=2). Proteobacteria dominated 90% of samples, with only one sample (P6) showing Firmicutes as predominant. Two pre-DNA extraction techniques were compared: a commercial kit and membrane vacuum filtration. The commercial kit detected E. coli in all samples and P. aeruginosa in 60%. The vacuum filtration technique found Burkholderiales (64%), Burkholderiaceae (81%), and Acidovorax (40%) to be predominant. The commercial kit showed higher Proteobacteria prevalence (>82%) and 100% Gammaproteobacteria. E. coli O157:H7 and Shigella flexneri 2a str. 301 were detected in all commercial kit samples and one vacuum filtration sample. Urban river source samples exhibited high bacterial diversity (615 genera, 736 species in P1; 640 genera, 802 species in P5) with a predominance of Alphaproteobacteria (52%). Samples from the rivers' final courses had reduced diversity (270 genera, 386 species in P2; 25 genera, 24 species in P6) and Gammaproteobacteria predominance. The comparison between the points before (UP) and after (DOWN) did not result in a noticeable correlation of influence from pig farming on the alteration of microbial composition in the samples. Our results highlight the presence of pathogenic bacteria in the aquatic environment surrounding pig farms and emphasize the potential threat to human, animal, and environmental health.

 

Karina L. Silva-Brandão¹, Julia Cabral Teresa², Clécio Fernando Klitzke, Marcelo M. Brandão³, José Roberto Trigo²

1 Leibniz Institute for the Analysis of Biodiversity Change, Museum of Nature Hamburg. Martin-Luther-King-Platz 3, 20421 Hamburg, Germany. Email: This email address is being protected from spambots. You need JavaScript enabled to view it.
2 Departamento de Biologia Animal, Instituto de Biologia, Universidade Estadual de Campinas. Rua Monteiro Lobato 255, Campinas, SP, Brazil.
3 Centro de Biologia Molecular e Engenharia Genética, Universidade Estadual de Campinas. Av. Cândido Rondon, 400, Campinas, SP, Brazil.

 Entomologia Experimentalis et Applicata 00: 1–12. https://doi.org/10.1111/eea.13589

The neotropical swallowtail butterfly Battus polydamas is a specialist on Aristolochia (Aristochiaceae). These plants are rich in natural products such as terpenoids, lignans, β-phenylethylamines (βPEA), aporphine and isoquinoline alkaloids, as well as aristolochic acids (AAs). Larvae of B. polydamas sequester some of these compounds, such as AAs, and transfer them to adults through the pupae. AAs are considered defensive compounds against natural enemies, however, the amount of AA in the larvae's diet has an effect on their performance, which may mean a cost to eating on AA-containing leaves. In the present study we evaluated the performance of B. polydamas larvae fed from 1^st instar through pupation on two host plants with different chemistry composition, A. ringens (which has several diterpenes) and A. gigantea (which has acyclic monoterpenoids and sesquiterpenoids, but no diterpenoids or AAs). Differential gene expression as response to different larval host plants was evaluated in three biological replications of gut and fat body tissues of six 5^th instar larvae. We found significant differences in the survival of larvae feeding on the two host plants; the survival in A. gigantea being significantly higher than survival in A. ringens (GLM binomial, likelihood ratio test, df = 1, χ² = 76.082, P < 0.001). In A. gigantea, 55% of the larvae persisted until pupation, while none of the larva feeding on A. ringens survived. 807 unique contigs identified by their molecular function were upregulated in the gut of larvae fed on A. ringens, while 298 were downregulated. Down-regulated contigs include genes encoding for ribosomal proteins, superoxide dismutase, P450s, UGTs, glutathione S-transferase and many proteases. Upregulated contigs comprise genes encoding for ribosomal proteins, protein farnesyltransferase, Phosphomevalonate kinase, Dolichyl-phosphate-mannose-protein mannosyltransferase 4 and O-glucosyltransferase (possibly involved in AAs metabolization). As expected, larvae of B. polydamas were strongly influenced by host plants exhibiting different concentrations of AAs, with higher concentrations leading to worse larval performance on key fitness components, such as life cycle performance attributes and larval survival. We suggest that there is a threshold of AA concentration in the host plant that larvae can tolerate, and above such a threshold the impact of plant secondary chemicals is no longer beneficial for the larvae, but negative, disrupting their detoxification mechanism.

Permanent link - https://url.bioinfoguy.net/battus2024

Data availability

It is necessary to properly cite the data repository (https://doi.org/10.25824/redu/A3GVHV) if you choose to utilise any of the data, script, or information provided in these files.