Tag Archives: Nucleotides

Novel computational platform can expand the pool of cancer immunotherapy targets

Researchers at Children’s Hospital of Philadelphia (CHOP) and the University of California, Los Angeles (UCLA) have developed a computational platform capable of discovering tumor antigens derived from alternative RNA splicing, expanding the pool of cancer immunotherapy targets. The tool, called “Isoform peptides from RNA splicing for Immunotherapy target Screening” (IRIS), was described in a paper published today in the Proceedings of the National Academy of Sciences.

Immunotherapy has revolutionized cancer treatment, but for many cancers including pediatric cancers, the repertoire of antigens is incomplete, underscoring a need to expand the inventory of actionable immunotherapy targets. We know that aberrant alternative RNA splicing is widespread in cancer and generates a range of potential immunotherapy targets. In our study, we were able to show that our computational platform was able to identify immunotherapy targets that arise from alternative splicing, introducing a broadly applicable framework for discovering novel cancer immunotherapy targets that arise from this process.”

Yi Xing, PhD, co-senior author, director of the Center for Computational and Genomic Medicine at CHOP

Cancer immunotherapy has ushered in a sea change in the treatment of many hematologic cancers, harnessing the power of a patient’s own immune system to fight the disease. Chimeric antigen receptor T-cell (CAR-T) and T cell receptor-engineered T cell (TCR-T) therapies modify a patient’s own T cells to attack known antigens on the surface of cancer cells and have often led to durable responses for cancers that were once considered incurable. However, the field has encountered challenges in the solid tumor space, in large part due to a lack of known and suitable targets for these cancers, highlighting the need for novel approaches to expand the pool of immunotherapy targets.

Alternative splicing is an essential process that allows for one gene to code for many gene products, based on where the RNA is cut and joined, or spliced, before being translated into proteins. However, the splicing process is dysregulated in cancer cells, which often take advantage of this process to produce proteins that promote growth and survival, allowing them to replicate uncontrollably and metastasize. This happens in many adult and pediatric cancers. Scientists have suggested splicing dysregulation could be a source of novel tumor antigens for immunotherapy, but identifying such antigens has been a challenge.

To address this difficulty, the researchers created IRIS to leverage large-scale tumor and normal RNA sequencing data and incorporate multiple screening approaches to discover tumor antigens that arise due to alternative splicing. Integrating RNA sequencing-based transcriptomics data and mass spectrometry-based proteomics data, the researchers showed that hundreds of IRIS-predicted TCR targets are presented by human leukocyte antigen (HLA) molecules, the part of the human immune system that presents antigens to T cells.

if (g_displayableSlots.mobileMiddleMrec) {
pushDisplayAd(function() { googletag.display(‘div-gpt-mobile-middle-mrec’); });

The researchers then applied IRIS to RNA sequencing data from neuroendocrine prostate cancer (NEPC), a metastatic and highly lethal disease known to involve shifts in RNA splicing, as discovered in a prior study by CHOP and UCLA researchers. From 2,939 alternative splicing events enriched in NEPC, IRIS predicted 1,651 peptides as potential TCR targets. The researchers then applied a more stringent screening test, which prioritized 48 potential targets. Interestingly, the researchers found that these targets were highly enriched for peptides encoded by short sequences of less than 30 nucleotides in length – also known as “microexons” – which may arise from a unique program of splicing dysregulation in this type of cancer.

To validate the immunogenicity of these targets, the researchers isolated T cells reactive to IRIS-predicted targets, and then used single-cell sequencing to identify the TCR sequences. The researchers modified human peripheral blood mononuclear cells with seven TCRs and found they were highly reactive against targets predicted by IRIS to be good immunotherapy candidates. One TCR was particularly efficient at killing tumor cells expressing the target peptide of interest.

“Immunotherapy is a powerful tool that has had a significant impact on the treatment of some cancers, but the benefits have not been fully realized in many lethal cancers that could benefit from this approach,” said Owen N. Witte, MD, University Professor of Microbiology, Immunology, and Molecular Genetics and member of the Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research at UCLA. “The discovery of new antigenic targets that may be shared among different patients – and even different tumor types – could be instrumental in expanding the value of cell-based therapies. Analyzing massive amounts of data on tumor and normal tissues, which requires sophisticated computational tools like those developed by the Xing Lab, provides actionable insights on targets that one day could be tested in the clinic.”

“This proof-of-concept study demonstrates that alternatively spliced RNA transcripts are viable targets for cancer immunotherapy and provides a big data and multiomics-powered computational platform for finding these targets,” Dr. Xing added. “We are applying IRIS for target discovery across a wide range of pediatric and adult cancers. We are also developing a next-generation IRIS platform that harnesses newer transcriptomics technologies, such as long read and single cell analysis.”

This research was supported in part by the Immuno-Oncology Translational Network (IOTN) of the National Cancer Institute’s Cancer Moonshot Initiative, other National Institutes of Health funding, the Parker Institute for Cancer Immunotherapy, the Cancer Research Institute, and the Ressler Family Fund.

Journal reference:

Pan, Y., et al. (2023) IRIS: Discovery of cancer immunotherapy targets arising from pre-mRNA alternative splicing. PNAS. doi.org/10.1073/pnas.2221116120.

Smoking alters lung microbiome, leading to loss of diversity and community structure

if (g_displayableSlots.mobileTopLeaderboard) {
pushDisplayAd(function() { googletag.display(‘div-gpt-mobile-top-leaderboard’); });

In a recent study published in the journal Access Microbiology, researchers explore the composition of the microbiome and interactions in the lower respiratory tract (LRT) in smokers. 

Study: Lower respiratory tract microbiome composition and community interactions in smokers. Image Credit: vchal / Shutterstock.com

The impact of smoking on the respiratory microbiome

Smoking has been shown to impact resident microbial communities present in different bodily regions. Previous studies have proposed various mechanisms responsible for this association, such as immunosuppression related to smoking, an increase in biofilm formation for specific species, and selection of species by the influence of local oxygen tension.

The upper airways and oral cavities may also directly interact with smoking chemicals, microbes, and heat from cigarettes, which can alter microbiome content. Recent studies have hypothesized that dysbiosis noted in the oral microbiome related to smoking may lead to a greater likelihood of experiencing complications in the respiratory tract among smokers. 

About the study

In the present study, researchers compare the LRT microbiome profiles of active smokers (AS), former smokers (FS), and non-smokers (NS) to describe the bacterial communities present in the lung.

The study involved volunteer subjects aged over 40 years of age who were either smokers of a minimum of 10 pack-years throughout their life or non-smokers. Former smokers qualified for the study if they had abstained from using tobacco for a minimum of 12 months, while AS smoked a minimum of one cigarette within three days of recruitment.

All study participants were required to complete a pulmonary function examination and thorough demographic and clinical questionnaire. The sampling process was standardized for all participants. The team extracted total deoxyribonucleic acid (DNA) from the bronchoalveolar lavages (BALs) specimens.

A single polymerase chain reaction (PCR) assessment was conducted to amplify the V6-V8 region present on the 16S ribosomal ribonucleic acid (rRNA) gene from the metagenomic DNA extracts of the BAL samples. Alpha diversity was estimated using Chao richness and inverse Simpson diversity indices. The DESeq2 algorithm was also used to detect differentiating taxa for each cohort.

if (g_displayableSlots.mobileMiddleMrec) {
pushDisplayAd(function() { googletag.display(‘div-gpt-mobile-middle-mrec’); });

Study findings

All 46 smokers reported similar smoking exposure in terms of pack-years, including the FS quitting smoking on an average of about 10 years prior to enrollment. AS and FS exhibited reduced forced vital capacity (FVC), diffusing capacity for carbon monoxide (DL-CO), and forced expiratory volume at second 1 (FEV1); however, these variations were not remarkable according to the analysis of variance (ANOVA).

Over 3,600 reads with an average length of about 479 nucleotides were documented in each participant’s BAL, which facilitated the description of almost 400 operational taxonomic units (OTUs) per participant. The NS profile was sufficiently balanced between the prevalent phyla Bacteroides, Firmicutes, Proteobacteria, and Actinobacteria with comparatively slightly higher proportions. The FS cohort had a significant increase in Proteobacteria with reduced Bacteroides and Firmicutes levels. This pattern was also true for AS, with Proteobacteria increasing to 75% and Firmicutes declining to 11%.

Genus-level assessments indicated that most of the enhancement in Proteobacteria in AS and FS in comparison to its high proportion in NS was due to the genus Ralstonia, which increased from 2% in the NS, 28% in AS, and 21% in FS.

From the Firmicutes phylum, the Streptococcus and Veillonella genera, as well as Prevotella from the Bacteroidetes phyla exhibited the greatest decline in comparative abundance. Furthermore, the Propionibacterium genus of the Actinobacteria phylum exhibited a slight improvement from 3% in AS and FS to 0.8% in NS.

With respect to the NS profile, a greater number of upper-quartile taxa were distinguished from AS, whereas lower-quartile taxa were distinguished from FS.

NS exhibited a considerably higher mean diversity as compared to AS and FS. The mean diversity further increased when the participants were placed by declining richness, thus indicating that NS reported higher richness. Yet, the diversity evaluated with the inverse Simpson index had only an intermediate association with richness estimates and the participant’s smoking status.


The current study provides new insights into the complicated microbial communities found in the LRT and how this microbiome can be changed under different smoking conditions. The researchers also observed that the oral microbiota can settle in the lungs of smokers, which makes the study of the upper airway microbiome interesting for future research.

The microbiomes of former smokers appear to exhibit similar properties to those of both AS and NS. In the future, integration of the present findings with next-generation analytical techniques would help establish the effect of such microbial communities on human health.

if (g_displayableSlots.mobileBottomLeaderboard) {
pushDisplayAd(function() { googletag.display(‘div-gpt-mobile-bottom-leaderboard’); });

Journal reference:
  • Campos, M., Cickovski, T., Fernandez, M., et al. (2023). Lower respiratory tract microbiome composition and community interactions in smokers. Access Microbiology. doi:10.1099/acmi.0.000497.v3

Do seasonal changes in food types lead to changes in the composition and structure of gut microbiota?

In a recent study published in the Frontiers in Microbiology, researchers assessed the impact of diet or macronutrient consumption on the function and structure of gut microbiota.

Study: Does diet or macronutrients intake drive the structure and function of gut microbiota? Image Credit: Alpha Tauri 3D Graphics/Shutterstock
Study: Does diet or macronutrients intake drive the structure and function of gut microbiota? Image Credit: Alpha Tauri 3D Graphics/Shutterstock


Shifting ingestive behavior is crucial for animals to adjust to environmental change. Studies have recognized that changes in animal feeding habits lead to gut microbiota structure alterations. However, further research is required to understand the alterations incident in the structure as well as the function of the gut microbiota that occur in response to alterations in nutrient consumption or food types.

About the study

In the present study, researchers explored how animal feeding techniques influence nutrient consumption and further affect the content and digestive function of the gut microbiota.

The study observation site was in the Guanyin Mountain National Natural Reserve in the Qinling Mountains, northwest of Fuping County, Shaanxi Province, China. During a year, this area experiences conventional and four different seasons. According to climate, the seasons are as follows: Spring between March and May, Summer between June and August, Autumn between September and November, and Winter between December and February.

The team compiled feeding information for the four seasonal groupings. For data collection, a month with typical phenological characteristics for each season: March for Spring, June for Summer, October for Autumn, and December for Winter.

All of the 78 golden snub-nosed monkeys in the study group were accustomed to the presence of researchers. The team identified both adult and young individuals in the study cohort. Due to the necessity for quantitative observational data, the natural feeding area of the study animals was restricted. The team provided five kilograms of maize twice daily at 10 am and 3 pm as supplemental nourishment for the group. The feed grounds were evenly strewn with corn kernels.

The team randomly selected one individual per day and observed the subject animal continuously from sunrise to dusk to record data related to its feeding pattern. Furthermore, the type of food, quantity, preset units, and feeding duration were recorded. After the subject had finished eating, food samples were gathered from the leftovers.

Food samples were collected using conventional procedures, their nutritional content was assessed, and their energy content was computed. The lipid, starch, water-soluble carbohydrate (WSC), acid detergent fiber (ADF), neutral detergent fiber (NDF), acid detergent lignin (ADL), ash content of each food, and available protein (AP) were evaluated.


Data related to 96 days of feeding across four months were obtained from the target population. It was discovered that the normal diet of golden snub-nosed monkeys in the wild comprised 24 plant species from 16 families. A total of six plant parts, including branches, buds, seeds, barks, leaves, and stems, were consumed by the subjects.

Throughout the year, wild snub-nosed monkeys eat 33.43% of bark, 3.09% of seed, 1.33% of bud, 3.25% of brunch, 0.17% of the stem, and 58.72% of the leaf. Nonetheless, there were significant variations in the number of plant materials consumed over the four seasons. Herbaceous stems were harvested only in tiny quantities in the Spring. Mostly, seeds were harvested in the Spring and fall. The harvesting of leaves occurred throughout the year. Throughout fall and Winter, when leaves become sparse, especially in Winter, barks, buds, and brunches were the principal sources of nutrition.

The species composition was evaluated to explore seasonal changes in gut microbiota in greater depth. Species annotation revealed that most OTUs could be assigned taxonomically at the phylum and order levels, but assignments reduced dramatically at the genus level.

The top 10 phyla out of 38 phyla recognized dominant phyla, including Bacteroidetes, Firmicutes, Spirochaetes, Proteobacteria, Tenericutes, Planctomycetes, Verrucomicrobia, Epsilonbacteriaeota, Euryarchaeota, and Fibrobacteres comprised 99% of the total abundance ratio. They comprised the majority of the golden snub-nosed monkeys’ gut microbiome.

Three hundred ninety-five metabolic pathways were found based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database’s function prediction. Gut microbes were primarily engaged in the metabolism of nucleotides, carbohydrates, glycans and their production, amino acids, terpenoids, lipids, cofactors, polyketides, and vitamins.

Moreover, some annotated functions pertaining to macronutrients exhibited relatively high abundance, including glycolysis/gluconeogenesis, pyruvate metabolism, sucrose and starch metabolism, glycerolipid metabolism, fatty acid synthesis in lipid metabolism, and pentose phosphate pathway in glycerophospholipid metabolism and carbohydrate metabolism.


The study findings showed a considerable seasonal change in the food consumption and nutritional intake of golden snub-nosed monkeys, with three macronutrients being higher in Autumn and Summer and lower in Winter and Spring. Seasonal dietary changes are the primary source of seasonal shifts in gut microbiota. The results indicated that bacteria in the gut compensate for inadequate macronutrient intake through microbial metabolic functions.

Journal reference:

Differences in gut microbiome diversity attributed to dietary patterns in children with obesity

In a recent study published in Microbiology Spectrum, researchers found that differences in the dietary patterns of children with normal weight and those who were overweight or obese contributed to variations in the gut microbiome diversity, virulence factors of gut bacteria, and metabolic function.

Study: Virulence factors of the gut microbiome are associated with BMI and metabolic blood parameters in children with obesity. Image Credit: Africa Studio / Shutterstock.com

Study: Virulence factors of the gut microbiome are associated with BMI and metabolic blood parameters in children with obesity. Image Credit: Africa Studio / Shutterstock.com


A growing body of evidence indicates that gut microbiota has a significant role in various aspects of host metabolism, including digestion, harvesting of energy, and induction of low-grade inflammation. In addition, the genetic factors of the host, as well as other characteristics such as age, diet, immunity, and gender, influence the gut microbiome composition.

Research shows that bacterial diversity in the gut and the individual’s functional capacity vary between those with normal weight and obese individuals. Gut microbiome profile variations have also been linked to metabolic disorders, lipid accumulation, and inflammation.

Lipogenesis in the liver and the regulation of appetite through hormones are also associated with gut microbiome genes.

Aside from its role in adipogenesis, superoxide reduction, and the metabolism of vitamins, gut microbiota also regulates innate immunity and the systemic, low-grade inflammatory state that can contribute to fat deposition and obesity. Therefore, Dysbiosis, which is the imbalance of gut microbiota, combined with diet, likely has a significant role in the development of obesity.

About the study

In the present study, researchers conducted a cross-sectional analysis of data from 45 children between the ages of six and 12 to determine the association between gut microbiota and obesity.

Questionnaires were used to obtain information on dietary frequencies, gender, age, and body mass index (BMI). Based on the World Health Organization (WHO) z-scores, in which BMI is adjusted for gender and age, the children were classified into two categories of overweight and obese (OWOB) and normal weight (NW).

Data from food frequency questionnaires were used to classify the dietary habits of children into two nutritional patterns. To this end, Pattern 1 was characterized by complex carbohydrates and proteins, whereas Pattern 2 comprised simple carbohydrates and saturated fats.

Shotgun metagenomics was used to assess the taxonomic diversity of the gut microbiota and metabolic capacity from genomic deoxyribonucleic acid (DNA) extracted from fecal samples. Clade-specific markers were used for the taxonomic and functional assessment of the gut bacteria. Additionally, reverse Simpson and Shannon diversity indices were calculated.

The virulence factor database was used to screen for virulence factor genes, whereas multivariate linear modeling was used to determine the association between the taxa, virulence factors, and function of gut microbes and covariates of diet, serology, and anthropometric measurements.

Study findings

Significant differences between the alpha and beta diversity of the gut microbiota were observed between the children in the NW and OWOB groups, thus suggesting that specific phyla of bacteria contribute to higher levels of energy harvest.

Furthermore, species such as Ruminococcus species, Victivallis vadensis, Mitsuokella multacida, Alistipes species, Clostridium species, and Acinetobacter johnsonii were linked to healthier metabolic parameters.

In contrast, an increase in the abundance of bacteria such as Veillonellaceae, Lactococcus, Fusicatenibacter saccharivorans, Fusicatenibacter prausnitzii, Eubacterium, Roseburia, Dialister, Coprococcus catus, Bifidobacterium, and Bilophila was identified in children with pro-inflammatory conditions and obesity.

Bacteria such as Citrobacter europaeus, Citrobacter youngae, Klebsiella variicola, Enterococcus mundtii, Gemella morbillorum, and Citrobacter portucalensis were associated with higher lipid and sugar intake, as well as higher blood biochemistry values and anthropometric measurements.

Diets high in fats and simple carbohydrates have been associated with the abundance of Citrobacter and Klebsiella species in the gut. Moreover, previous studies have indicated that these bacterial species are potential markers of inflammation, obesity, and an increase in fasting glucose.

The metabolism of menaquinones and gamma-glutamyl was negatively associated with BMI. Furthermore, the microbiomes of children in the NW group preserved a more consistent alpha diversity of virulence factors, while OWOB microbiomes exhibited a dominance of virulence factors.

Differences in the metabolic capacities pertaining to biosynthesis pathways of vitamins, carriers, amino acids, nucleotides, nucleosides, amines, and polyamines, as well as the degradation of nucleotides, nucleosides, and carbohydrate-sugars, were also found between the NW and OWOB groups.


Dietary profiles and the diversity of gut microbiota were found to be interconnected and associated with changes in metabolic parameters, the dominance of virulence factors, and obesity. Changes in gut microbiome diversity and relative abundance have been linked to obesity, inflammatory responses, and metabolic disorders.

Taken together, the study findings suggested that the prevalence of virulence factors, as well as the metabolic and genetic roles of gut microbiota in increasing inflammation, can help identify individuals at an increased risk of childhood obesity.

Journal reference:
  • Murga-Garrido, S. M., Ulloa-Pérez, E. J., Díaz-Benítez, C. E., et al. (2023). Virulence factors of the gut microbiome are associated with BMI and metabolic blood parameters in children with obesity. Microbiology Spectrum. doi:10.1128/spectrum.03382-22

Researchers discover new role of small RNAs in Salmonella infections

Salmonella are food-borne pathogens that infect millions of people a year. To do so, these bacteria depend on a complex network of genes and gene products that allow them to sense environmental conditions. In a new paper, researchers have investigated the role of small RNAs that help Salmonella express their virulence genes.

The bacteria infect humans by first invading the cells of the intestine using a needle-like structure, called a type 3 secretion system. This structure injects proteins directly into the cells, setting off a cascade of changes that cause inflammation, and ultimately cause diarrhea. The genes that encode this system, and other genes that are needed for invasion, are found on a region of DNA known as the Salmonella pathogenicity island 1.

SPI-1 needs to be well controlled. If the type 3 secretion system needle apparatus is not made, Salmonella cannot cause an infection, and if too much of the needle apparatus is made, it makes Salmonella sick.”

Sabrina Abdulla, a graduate student in the Vanderpool lab, and the first author of the study

SPI-1 is controlled by an extensive regulatory network. First, three transcription factors: HilD, HilC, and RtsA, all control their own and each other’s DNA expression. They also activate another transcription factor, HilA, which activates the rest of the SPI-1 genes. If this isn’t complicated enough, SPI-1 also needs to sense a variety of environmental cues and tune the expression of its genes in order to infect its host.

“We have known for a long time that there are a lot of environmental factors that feed into the gene regulation in Salmonella. However, we didn’t know how. That’s when researchers started looking at small RNAs,” Abdulla said.

Small RNAs play a crucial role in determining how genes function in bacterial cells. Typically, these molecules either interact with proteins, or the mRNA, which carries the instructions for making proteins. As a result, sRNAs affect a variety of bacterial functions, including virulence and responses to the environment.

In this paper, the researchers looked at the sRNAs that regulate the hilD mRNA, specifically a sequence on the mRNA called the 3′ untranslated region, a part of the mRNA not involved in making the HilD protein. In bacteria, the 3′ UTRs are usually 50-100 nucleotides long. However, the 3′ UTR of the hilD mRNA was 300 nucleotides long.

“The starting point for my work was the observation that when we deleted the 3′ UTR, the expression of the hilD gene went up 60-fold,” Abdulla said. “We then decided to look for sRNAs that might be interacting with this region.”

The researchers determined that although the sRNAs Spot 42 and SdsR can both target the 3′ UTR, they do so in different regions. “This result suggests that the entire 3′ UTR is important for regulation,” Abdulla said. “We showed that the sRNAs stabilize the hilD mRNA and protect it from being degraded.”

“Such long 3′ UTRs have not been well studied. With more genomic research, people are realizing more and more that these longer regions exist and that they are important for regulation,” Abdulla said.

Using mice, the researchers also looked at whether Spot 42 and SdsR can affect how Salmonella causes infections. They performed mouse competition assays, where they introduced mutant bacteria that lacked the sRNAs and bacteria that contained the sRNAs, to see which strains survive and cause infection. “We found that when the sRNAs are deleted, the bacteria cannot survive in the host. We also showed that the sRNAs play a role in helping SPI-1 invade the host cells,” Abdulla said.

“Now that we know that sRNAs play an important role in controlling SPI-1 through their regulatory effects on the hilD 3′ UTR, we want to extend our studies in two directions. We’d like to understand more about how, at a molecular level, the sRNAs influence hilD mRNA levels. We’d also like to better understand how sRNAs participate in regulating expression of other important SPI-1 genes,” said Cari Vanderpool (MME/IGOH), a professor of microbiology.

Journal reference:

Abdulla, S.Z., et al. (2022) Small RNAs Activate Salmonella Pathogenicity Island 1 by Modulating mRNA Stability through the hilD mRNA 3′ Untranslated Region. Journal of Bacteriology. doi.org/10.1128/jb.00333-22.