Glycomic analysis of host-response reveals high mannose as a key mediator of influenza severity

Heindel, Daniel W.; Koppolu, Sujeethraj; Zhang, Yue; Kasper, Brian; Meche, Lawrence; Vaiana, Christopher A.; Bissel, Stephanie J.; Carter, Chalise E.; Kelvin, Alyson A.; Zhang, Bin; Zhou, Bin; Chu, Tsui-Wen; Lashua, Lauren; Ross, Ted M.; Ghedin, Elodie; Mahal, Lara K.

doi:10.1101/2020.04.21.054098

Cited by 10 publications

(22 citation statements)

References 54 publications

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“…Lectin microarrays, in which a panel of lectins (10s to >100) and other carbohydrate-binding probes (e.g., antibodies) are printed on a solid support, are now routinely used in glycomics [5][6][7]. This high-throughput method has identified glycans involved in a variety of systems from melanoma metastasis to viral host-response [8][9][10]. Although lectins are useful tools, they have suffered from a lack of detailed definition of their binding requirements, which hampers their use analytically.…”

Section: Introductionmentioning

confidence: 99%

A Useful Guide to Lectin Binding: Machine-Learning Directed Annotation of 57 Unique Lectin Specificities

Bojar

Meche

Meng

et al. 2021

Preprint

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Glycans are critical to every facet of biology and medicine, from viral infections to embryogenesis. Tools to study glycans are rapidly evolving, however the majority of our knowledge is deeply dependent on binding by glycan binding proteins (e.g., lectins). The specificities of lectins, which are often naturally isolated proteins, have not been well- defined, making it difficult to leverage their full potential for glycan analysis. Herein, we use glycan microarray analysis of 116 commercially available lectins, including different preparations of the same lectin, to extract the specific glycan features required for lectin binding. Data was obtained using the Consortium for Functional Glycomics microarray (CFG v5.0) containing 611 glycans. We use a combination of machine learning algorithms to define lectin specificity, mapping inputs (glycan sequences) to outputs (lectin-glycan binding) for a large-scale evaluation of lectin-glycan binding behaviours. Our motif analysis was performed by integrating 68 manually defined glycan features with systematic probing of computational rules for significant binding motifs using mono- and disaccharides- and linkages. Using a combination of machine learning and manual annotation of the data, we created a detailed interpretation of glycan-binding specificity for 57 unique lectins, categorized by their major binding motifs: mannose, complex-type N-glycan, O-glycan, fucose, sialic acid and sulfate, GlcNAc and chitin, Gal and LacNAc, and GalNAc. Our work provides fresh insights into the complex binding features of commercially available lectins in current use, providing a critical guide to these important reagents.

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Section: Introductionmentioning

confidence: 99%

A Useful Guide to Lectin Binding: Machine-Learning Directed Annotation of 57 Unique Lectin Specificities

Bojar

Meche

Meng

et al. 2021

Preprint

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“…In recent work, our laboratory analyzed the glycomic response to H1N1pdm09 in an adult ferret population using our lectin microarray technology. 15 We found that the severity was not related to sialic acid levels but, rather, correlated with the expression of high mannose N-glycans. Histology on ferret lungs showed high mannose levels corresponded with alveolar severity and was present throughout the tissue on multiple cell types.…”

Section: Introductionmentioning

confidence: 67%

“…We observed several changes in aged ferrets as a function of infection that did not overlay onto severity. For ease of comparison between the aged and adult host responses, we reanalyzed the lectin microarray data from our adult ferret cohort 15 using PCS as the severity metric. In our previous work, adult ferrets showed an increase in α-2,6 sialylation at early infection time points, with levels returning to baseline by day 8 postinfection.…”

Section: Resultsmentioning

confidence: 99%

“…Our recent work strongly suggests a role for high/oligo-mannose as a key mediator of influenza severity. 15 In our original analysis, the severity in the adult ferrets was defined by weight loss. Reanalysis of these data using pneumonia composite scores did not change the previously observed relationship between the high/oligo-mannose levels and severity ( Supporting Information , Figure S12).…”

Section: Resultsmentioning

confidence: 99%

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Age-Dependent Glycomic Response to the 2009 Pandemic H1N1 Influenza Virus and Its Association with Disease Severity

et al. 2020

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Influenza A viruses cause a spectrum of responses, from mild coldlike symptoms to severe respiratory illness and death. Intrinsic host factors, such as age, can influence disease severity. Glycosylation plays a critical role in influenza pathogenesis; however, the molecular drivers of influenza outcomes remain unknown. In this work, we characterized the host glycomic response to the H1N1 2009 pandemic influenza A virus (H1N1pdm09) as a function of age-dependent severity in a ferret model. Using our dual-color lectin microarray technology, we examined baseline glycosylation and glycomic response to infection in newly weaned and aged animals, models for young children and the elderly, respectively. Compared to adult uninfected ferrets, we observed higher levels of α-2,6-sialosides, the receptor for H1N1pdm09, in newly weaned and aged animals. We also observed age-dependent loss of O-linked α-2,3-sialosides. The loss of these highly charged groups may impact viral clearance by mucins, which corresponds to the lower clearance rates observed in aged animals. Upon infection, we observed dramatic changes in the glycomes of aged animals, a population severely impacted by the virus. In contrast, no significant alterations were observed in the newly weaned animals, which show mild to moderate responses to the H1N1pdm09. High mannose, a glycan recently identified as a marker of severity in adult animals, increased with severity in the aged population. However, the response was delayed, in line with the delayed development of pneumonia observed. Overall, our results may help explain the differential susceptibility to influenza A infection and severity observed as a function of age.

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“…7 For influenza, the high-mannose motif on infected host cells guides immune responses leading to the concomitant damage associated with disease severity. 8 Recently, high-mannose glycans have been implicated in supporting cholangiocarcinoma metastasis by enhancing the ability to translocate, invade surrounding basement membrane matrix and migrate through micropores. 9 In all eukaryotic cells, GDP-Man is synthesized in cytosol (Figure 1B), and used in endoplasmic reticulum (ER) to support highly organized mannosylation of dolichols and glycoproteins (Figure 1C).…”

Section: Introductionmentioning

confidence: 99%

³¹P‐MRS of healthy human brain: Measurement of guanosine diphosphate mannose at 7 T

Ren

Sherry

2021

NMR in Biomedicine

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Guanosine diphosphate mannose (GDP-Man) is the donor substrate required for mannosylation in the synthesis of glycoproteins, glycolipids and the newly discovered glycoRNA. Normal GDP-Man biosynthesis plays a crucial role in support of a variety of cellular functions, including cell recognition, cell communication and immune responses against viruses. Here, we report the detection of GDP-Man in human brain for the first time, using 31 P MRS at 7 T. The presence of GDP-Man is evidenced by the detection of a weak 31 P doublet at À10.7 ppm that can be assigned to the phosphomannosyl group (Pβ) of the GDP-Man molecule. This weak but well-resolved signal lies 0.9 ppm upfield of UDP(G) Pβ-multiplet from a mixture of UDP-Glc, UDP-Gal, UDP-GlcNAc and UDP-GalNAc. In reference to ATP (2.8 mM), the concentration of GDP-Man in human brain was estimated to be 0.02 ± 0.01 mM, about 15-fold lower than the total concentration of UDP(G) (0.30 ± 0.04, N = 17) and consistent with previous reports of UDP-Man in cells and brain tissue extracts measured by highperformance liquid chromatography. The reproducibility of the measured GDP-Man between test and 2-week retest was 21% ± 15% compared with 5% ± 4% for UDP(G) (N = 7). The measured concentrations of GDP-Man and UDP(G) are linearly correlated ([UDP(G)] = 4.3 [GDP-Man] + 0.02, with R = 0.66 and p = 0.0043), likely reflecting the effect of shared sugar precursors, which may vary among individuals in response to variation in nutritional intake and consumption. Given that GDP-Man has another set of doublet (Pα) at À8.3 ppm that overlaps with NAD(H) and UDP(G)-Pα signals, the amount of GDP-Man could potentially interfere with the deconvolution of these mixed signals in composition analysis. Importantly, this new finding may be useful in advancing our understanding of glycosylation and its role in the development of cancer, as well as infectious and neurodegenerative diseases.

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Glycomic analysis of host-response reveals high mannose as a key mediator of influenza severity

Abstract: 1

Cited by 10 publications

References 54 publications

A Useful Guide to Lectin Binding: Machine-Learning Directed Annotation of 57 Unique Lectin Specificities

A Useful Guide to Lectin Binding: Machine-Learning Directed Annotation of 57 Unique Lectin Specificities

Age-Dependent Glycomic Response to the 2009 Pandemic H1N1 Influenza Virus and Its Association with Disease Severity

³¹P‐MRS of healthy human brain: Measurement of guanosine diphosphate mannose at 7 T

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Glycomic analysis of host-response reveals high mannose as a key mediator of influenza severity

Abstract: 1

Cited by 10 publications

References 54 publications

A Useful Guide to Lectin Binding: Machine-Learning Directed Annotation of 57 Unique Lectin Specificities

A Useful Guide to Lectin Binding: Machine-Learning Directed Annotation of 57 Unique Lectin Specificities

Age-Dependent Glycomic Response to the 2009 Pandemic H1N1 Influenza Virus and Its Association with Disease Severity

31P‐MRS of healthy human brain: Measurement of guanosine diphosphate mannose at 7 T

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³¹P‐MRS of healthy human brain: Measurement of guanosine diphosphate mannose at 7 T