In-depth qualitative and quantitative analysis of composite glycosylation profiles and other micro-heterogeneity on intact monoclonal antibodies by high-resolution native mass spectrometry using a modified Orbitrap

Here, we describe a fast, easy-to-use, and sensitive method to profile in-depth structural micro-heterogeneity, including intricate N-glycosylation profiles, of monoclonal antibodies at the native intact protein level by means of mass spectrometry using a recently introduced modified Orbitrap Exactive Plus mass spectrometer. We demonstrate the versatility of our method to probe structural micro-heterogeneity by describing the analysis of three types of molecules: (1) a non-covalently bound IgG4 hinge deleted full-antibody in equilibrium with its half-antibody, (2) IgG4 mutants exhibiting highly complex glycosylation profiles, and (3) antibody-drug conjugates. Using the modified instrument, we obtain baseline separation and accurate mass determination of all different proteoforms that may be induced, for example, by glycosylation, drug loading and partial peptide backbone-truncation. We show that our method can handle highly complex glycosylation profiles, identifying more than 20 different glycoforms per monoclonal antibody preparation and more than 30 proteoforms on a single highly purified antibody. In analyzing antibody-drug conjugates, our method also easily identifies and quantifies more than 15 structurally different proteoforms that may result from the collective differences in drug loading and glycosylation. The method presented here will aid in the comprehensive analytical and functional characterization of protein micro-heterogeneity, which is crucial for successful development and manufacturing of therapeutic antibodies     

HIPPI: highly accurate protein family classification with ensembles of HMMs

Background

Given a new biological sequence, detecting membership in a known family is a basic step in many bioinformatics analyses, with applications to protein structure and function prediction and metagenomic taxon identification and abundance profiling, among others. Yet family identification of sequences that are distantly related to sequences in public databases or that are fragmentary remains one of the more difficult analytical problems in bioinformatics.

Results

We present a new technique for family identification called HIPPI (Hierarchical Profile Hidden Markov Models for Protein family Identification). HIPPI uses a novel technique to represent a multiple sequence alignment for a given protein family or superfamily by an ensemble of profile hidden Markov models computed using HMMER. An evaluation of HIPPI on the Pfam database shows that HIPPI has better overall precision and recall than blastp, HMMER, and pipelines based on HHsearch, and maintains good accuracy even for fragmentary query sequences and for protein families with low average pairwise sequence identity, both conditions where other methods degrade in accuracy.

Conclusion

HIPPI provides accurate protein family identification and is robust to difficult model conditions. Our results, combined with observations from previous studies, show that ensembles of profile Hidden Markov models can better represent multiple sequence alignments than a single profile Hidden Markov model, and thus can improve downstream analyses for various bioinformatic tasks. Further research is needed to determine the best practices for building the ensemble of profile Hidden Markov models. HIPPI is available on GitHub at https://github.com/smirarab/sepp.

     

Ouabain-insensitive salt and water movements in duck red cells. II. Norepinephrine stimulation of sodium plus potassium cotransport

Catecholamines induce net salt and water movements in duck red cells incubated in isotonic solutions. The rate of this response is approximately three times greater than a comparable effect observed in 400 mosmol hypertonic solutions in the absence of hormone (W.F. Schmidt and T. J. McManus. 1977 a.J. Gen. Physiol. 70:59-79. Otherwise, these two systems share a great many similarities. In both cases, net water and salt movements have a marked dependence on external cation concentrations, are sensitive to furosemide and insensitive to ouabain, and allow the substitution of rubidium for external potassium. In the presence of ouabain, but the absence of external potassium (or rubidium), a furosemide-sensitive net extrusion of sodium against a large electrochemical gradient can be demonstrated. When norepinephrine-treated cells are incubated with ouabain and sufficient external sodium, the furosemide-sensitive, unidirectional influxes of both sodium and rubidium are half- maximally saturated at similar rubidium concentrations; with saturating external rubidium, the same fluxes are half-maximal at comparable levels of external sodium. In the absence of sodium, a catecholamine-stimulated, furosemide-sensitive influx of rubidium persists. In the absence of rubidium, a similar but smaller component of sodium influx can be seen. We interpret these results in terms of a cotransport model for sodium plus potassium which is activated by hypertonicity or norepinephrine. When either ion is absent from the incubation medium, the system promotes an exchange-diffusion type of movement of the co-ion into the cells. In the absence of external potassium, net movement of potassium out of the cell leads to a coupled extrusion of sodium against its electrochemical gradient.     

New approaches for reconstructing phylogenies from gene order data

We report on new techniques we have developed for reconstructing phylogenies on whole genomes. Our mathematical techniques include new polynomial-time methods for bounding the inversion length of a candidate tree and new polynomial-time methods for estimating genomic distances which greatly improve the accuracy of neighbor-joining analyses. We demonstrate the power of these techniques through an extensive performance study based on simulating genome evolution under a wide range of model conditions. Combining these new tools with standard approaches (fast reconstruction with neighbor-joining, exploration of all possible refinements of strict consensus trees, etc.) has allowed us to analyze datasets that were previously considered computationally impractical. In particular, we have conducted a complete phylogenetic analysis of a subset of the Campanulaceae family, confirming various conjectures about the relationships among members of the subset and about the principal mechanism of evolution for their chloroplast genome. We give representative results of the extensive experimentation we conducted on both real and simulated datasets in order to validate and characterize our approaches. We find that our techniques provide very accurate reconstructions of the true tree topology even when the data are generated by processes that include a significant fraction of transpositions and when the data are close to saturation.     

Unidentifiable divergence times in rates-across-sites models

The rates-across-sites assumption in phylogenetic inference posits that the rate matrix governing the Markovian evolution of a character on an edge of the putative phylogenetic tree is the product of a character-specific scale factor and a rate matrix that is particular to that edge. Thus, evolution follows basically the same process for all characters, except that it occurs faster for some characters than others. To allow estimation of tree topologies and edge lengths for such models, it is commonly assumed that the scale factors are not arbitrary unknown constants, but rather unobserved, independent, identically distributed draws from a member of some parametric family of distributions. A popular choice is the gamma family. We consider an example of a clock-like tree with three taxa, one unknown edge length, a known root state, and a parametric family of scale factor distributions that contains the gamma family. This model has the property that, for a generic choice of unknown edge length and scale factor distribution, there is another edge length and scale factor distribution which generates data with exactly the same distribution, so that even with infinitely many data it will be typically impossible to make correct inferences about the unknown edge length.     

Enzymic synthesis,chemical characterisation and Sda activity of GalNAcß1-4[NeuAcα2-3]Galß1-4GlcNAc and GalNAcß1-4[NeuAcα2-3]Galß1-4Glc

The tetrasaccharides GalNAcß1-4[NeuAc2-3]Galß1-4Glc and GalNAcß1-4[NeuAc2-3]Galß1-4GlcNAc were synthesised by enzymic transfer of GalNAc from UDP-GalNAc to 3-sialyllactose (NeuAc2-3Galß1-4Glc) and 3-sialyl-N-acetyllactosamine (NeuAc2-3Galß1-4GlcNAc). The structures of the products were established by methylation and¹H-500 MHz NMR spectroscopy. In Sd^a serological tests the product formed with 3-sialyl-N-acetyllactosamine was highly active whereas that formed with 3-sialyllactose had only weak activity.     

Algorithms for MDC-based multi-locus phylogeny inference: beyond rooted binary gene trees on single alleles

One of the criteria for inferring a species tree from a collection of gene trees, when gene tree incongruence is assumed to be due to incomplete lineage sorting (ILS), is Minimize Deep Coalescence (MDC). Exact algorithms for inferring the species tree from rooted, binary trees under MDC were recently introduced. Nevertheless, in phylogenetic analyses of biological data sets, estimated gene trees may differ from true gene trees, be incompletely resolved, and not necessarily rooted. In this article, we propose new MDC formulations for the cases where the gene trees are unrooted/binary, rooted/non-binary, and unrooted/non-binary. Further, we prove structural theorems that allow us to extend the algorithms for the rooted/binary gene tree case to these cases in a straightforward manner. In addition, we devise MDC-based algorithms for cases when multiple alleles per species may be sampled. We study the performance of these methods in coalescent-based computer simulations.     

The species–area relationship in centipedes (Myriapoda: Chilopoda): a comparison between Mediterranean island groups

The present study article examines the shapes of centipede species–area relationships (SARs) in the Mediterranean islands, compares the results of the linear form of the power model between archipelagos, discusses biological significance of the power model parameters with other taxa on the Aegean archipelago, and tests for a significant small‐island effect (SIE). We used 11 models to test the SARs and we compared the quality‐of‐fit of all candidate models. The power function ranked first and Z‐values was in the range 0.106–0.334. We assessed the presence of SIEs by fitting both a continuous and discontinuous breakpoint regression model. The continuous breakpoint regression functions never performed much better than the closest discontinuous model as a predictor of centipede species richness. We suggest that the relatively low Z‐values in our data partly reflect better dispersal abilities in centipedes than in other soil invertebrate taxa. Longer periods of isolation and more recent island formation may explain the somewhat lower constant c in the western Mediterranean islands compared to the Aegean islands. Higher breakpoint values in the western Mediterranean may also be a result of larger distance to the mainland and longer separation times. Despite the differences in the geological history and the idiosyncratic features of the main island groups considered, the overall results are quite similar and this could be assigned to the ability of centipedes to disperse across isolation barriers. © 2011 The Linnean Society of London, Biological Journal of the Linnean Society, 2012, 105 , 146–159.