Archaea Microbiome Dysregulated Genes and Pathways as Molecular Targets for Lung Adenocarcinoma and Squamous Cell Carcinoma

Uzelac, Matthew; Li, Yuxiang; Chakladar, Jaideep; Li, Wei Tse; Ongkeko, Weg M.

doi:10.3390/ijms231911566

Cited by 6 publications

(3 citation statements)

References 39 publications

(63 reference statements)

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“…Pathoscope2 can identify strains, compute abundance levels, perform re-assignments, and output informative result summaries. It has seen usage in numerous studies [ 22 – 25 ], and its algorithm has also been incorporated into other taxonomic classification pipelines [ 16 ]. Kraken2 and Clark are two taxonomic classifiers that classify reads by assigning them a taxonomic ID.…”

Section: Resultsmentioning

confidence: 99%

Mora: abundance aware metagenomic read re-assignment for disentangling similar strains

Zheng,

Shaw,

2024

BMC Bioinformatics

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Background Taxonomic classification of reads obtained by metagenomic sequencing is often a first step for understanding a microbial community, but correctly assigning sequencing reads to the strain or sub-species level has remained a challenging computational problem. Results We introduce Mora, a MetagenOmic read Re-Assignment algorithm capable of assigning short and long metagenomic reads with high precision, even at the strain level. Mora is able to accurately re-assign reads by first estimating abundances through an expectation-maximization algorithm and then utilizing abundance information to re-assign query reads. The key idea behind Mora is to maximize read re-assignment qualities while simultaneously minimizing the difference from estimated abundance levels, allowing Mora to avoid over assigning reads to the same genomes. On simulated diverse reads, this allows Mora to achieve F1 scores comparable to other algorithms while having less runtime. However, Mora significantly outshines other algorithms on very similar reads. We show that the high penalty of over assigning reads to a common reference genome allows Mora to accurately infer correct strains for real data in the form of E. coli reads. Conclusions Mora is a fast and accurate read re-assignment algorithm that is modularized, allowing it to be incorporated into general metagenomics and genomics workflows. It is freely available at https://github.com/AfZheng126/MORA.

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Section: Resultsmentioning

confidence: 99%

Mora: abundance aware metagenomic read re-assignment for disentangling similar strains

Zheng,

Shaw,

2024

BMC Bioinformatics

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“…Pathoscope2 can identify strains, compute abundance levels, perform re-assignments, and output informative result summaries. It has seen usage in numerous studies [32,9,13,26] and its algorithm has also been incorporated into other taxonomic classification pipelines [8]. Kraken2 and Clark are two taxonomic classifiers that classify reads by assigning them a taxonomic ID.…”

Section: Resultsmentioning

confidence: 99%

Mora: abundance aware metagenomic read re-assignment for disentangling similar strains

Zheng

Shaw

2022

Preprint

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Taxonomic classification of reads obtained by metagenomic sequencing is often a first step for understanding a microbial community. While species level classification has become routine, correctly assigning sequencing reads to the strain or sub-species level has remained a challenging computational problem. We introduce Mora, a MetagenOmic read Re-Assignment algorithm capable of assigning short and long metagenomic reads with high precision, even at the strain level. Mora is able to accurately re-assign reads by first estimating abundances through an expectation-maximization algorithm and then utilizing abundance information to re-assign query reads. The key idea behind Mora is to maximize read re-assignment qualitieswhile simultaneouslyminimizing the difference from estimated abundance levels, allowing Mora to avoid over assigning reads to the same genomes. On simulated data, this allows Mora to achieve F1 scores of > 74% when assigning reads generated from three distinct E. coli strains, much higher than the 29% and 32% achieved by Pathoscope2 and Pufferfish. Furthermore, we show that the high penalty of over assigning reads to a common reference genome allows Mora to accurately identify the presence of low abundance strains and species.Code availabilityhttps://github.com/AfZheng126/MORA

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“…So far, studies of the archaeome in cancer have been limited to colorectal cancer [ 56 , 57 ]. Thus, our investigation of the archaeometry in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) was the first to associate archaeal microbes with pertinent metabolic and oncogenic pathways in any non-colorectal cancer [ 58 ]. In this paper, we found that intratumor archaeal species were distinctly dysregulated between LUAD and LUSC samples and exhibited associations with unique cellular pathway regulation and clinical progression variables.…”

Section: Discussionmentioning

confidence: 99%

Transcriptomic Analysis Reveals Dysregulation of the Mycobiome and Archaeome and Distinct Oncogenic Characteristics according to Subtype and Gender in Papillary Thyroid Carcinoma

John

Yalamarty

Barakchi

et al. 2023

IJMS

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Papillary Thyroid Carcinoma (PTC) is characterized by unique tumor morphology, treatment response, and patient outcomes according to subtype and gender. While previous studies have implicated the intratumor bacterial microbiome in the incidence and progression of PTC, few studies have investigated the potential role of fungal and archaeal species in oncogenesis. In this study, we aimed to characterize the intratumor mycobiome and archaeometry in PTC with respect to its three primary subtypes: Classical (CPTC), Follicular Variant (FVPTC), and Tall Cell (TCPTC), and also with respect to gender. RNA-sequencing data were downloaded from The Cancer Genome Atlas (TCGA), including 453 primary tumor tissue samples and 54 adjacent solid tissue normal samples. The PathoScope 2.0 framework was used to extract fungal and archaeal microbial read counts from raw RNA-sequencing data. Overall, we found that the intratumor mycobiome and archaeometry share significant similarities in CPTC, FVPTC, and TCPTC, although most dysregulated species in CPTC are underabundant compared to normal. Furthermore, differences between the mycobiome and archaeometry were more significant between males and females, with a disproportionate number of fungal species overabundant in female tumor samples. Additionally, the expression of oncogenic PTC pathways was distinct across CPTC, FVPTC, and TCPTC, indicating that these microbes may uniquely contribute to PTC pathogenesis in each subtype. Furthermore, differences in the expression of these pathways were observed between males and females. Finally, we found a specific panel of fungi to be dysregulated in BRAF V600E-positive tumors. This study demonstrates the potential importance of microbial species to PTC incidence and oncogenesis.

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Archaea Microbiome Dysregulated Genes and Pathways as Molecular Targets for Lung Adenocarcinoma and Squamous Cell Carcinoma

Cited by 6 publications

References 39 publications

Mora: abundance aware metagenomic read re-assignment for disentangling similar strains

Mora: abundance aware metagenomic read re-assignment for disentangling similar strains

Mora: abundance aware metagenomic read re-assignment for disentangling similar strains

Transcriptomic Analysis Reveals Dysregulation of the Mycobiome and Archaeome and Distinct Oncogenic Characteristics according to Subtype and Gender in Papillary Thyroid Carcinoma

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