Nucleotide binding-promoted conformational changes release a nonnative polypeptide from the Escherichia coli chaperonin GroEL.

The Escherichia coli chaperonins GroEL and GroES facilitate the refolding of polypeptide chains in an ATP hydrolysis-dependent reaction. The elementary steps in the binding and release of polypeptide substrates to GroEL were investigated in surface plasmon resonance studies to measure the rates of binding and dissociation of a normative variant of subtilisin. The rate constants determined for GroEL association with and dissociation from this variant yielded a micromolar dissociation constant, in agreement with independent calorimetric estimates. The rate of GroEL dissociation from the nonnative chain was increased significantly in the presence of 5'-adenylylimidodiphosphate (AMP-PNP), ADP, and ATP, yielding maximal values between 0.04 and 0.22 s(-1). The sigmoidal dependence of the dissociation rate on the concentration of AMP-PNP and ADP indicated that polypeptide dissociation is limited by a concerted conformational change that occurs after nucleotide binding. The dependence of the rate of release on ATP exhibited two sigmoidal transitions attributable to nucleotide binding to the distal and proximal toroid of a GroEL-polypeptide chain complex. The addition of GroES resulted in a marked increase in the rate of nonnative polypeptide release from GroEL, indicating that the cochaperonin binds more rapidly than the dissociation of polypeptides. These data demonstrate the importance of nucleotide binding-promoted concerted conformational changes for the release of chains from GroEL, which correlate with the sigmoidal hydrolysis of ATP by the chaperonin. The implications of these findings are discussed in terms of a working hypothesis for a single cycle of chaperonin action.

Folding in vivo of a newly translated yeast cytosolic enzyme is mediated by the SSA class of cytosolic yeast Hsp70 proteins

The nature of chaperone action in the eukaryotic cytosol that assists newly translated cytosolic proteins to reach the native state has remained poorly defined. Actin, tubulin, and Gα transducin are assisted by the cytosolic chaperonin, CCT, but many other proteins, for example, ornithine transcarbamoylase (OTC), a cytosolic homotrimeric enzyme of yeast, do not require CCT action. Here, we observe that yeast cytosolic OTC is assisted to its native state by the SSA class of yeast cytosolic Hsp70 proteins. In vitro, refolding of OTC diluted from denaturant was assisted by crude yeast cytosol and ATP and found to be directed by SSA1/2. In vivo, when OTC was induced in a temperature-sensitive SSA-deficient strain, it exhibited reduced specific activity, and nonnative subunits were detected in the soluble fraction. These findings indicate that, in vivo, the Hsp70 system assists in folding at least some newly translated cytosolic enzymes, most likely functioning in a posttranslational manner.

Specific binding of proinsulin C-peptide to human cell membranes

Recent reports have demonstrated beneficial effects of proinsulin C-peptide in the diabetic state, including improvements of kidney and nerve function. To examine the background to these effects, C-peptide binding to cell membranes has been studied by using fluorescence correlation spectroscopy. Measurements of ligand–membrane interactions at single-molecule detection sensitivity in 0.2-fl confocal volume elements show specific binding of fluorescently labeled C-peptide to several human cell types. Full saturation of the C-peptide binding to the cell surface is obtained at low nanomolar concentrations. Scatchard analysis of binding to renal tubular cells indicates the existence of a high-affinity binding process with Kass > 3.3 × 109 M−1. Addition of excess unlabeled C-peptide is accompanied by competitive displacement, yielding a dissociation rate constant of 4.5 × 10−4 s−1. The C-terminal pentapeptide also displaces C-peptide bound to cell membranes, indicating that the binding occurs at this segment of the ligand. Nonnative d-C-peptide and a randomly scrambled C-peptide do not compete for binding with the labeled C-peptide, nor were crossreactions observed with insulin, insulin-like growth factor (IGF)-I, IGF-II, or proinsulin. Pretreatment of cells with pertussis toxin, known to modify receptor-coupled G proteins, abolishes the binding. It is concluded that C-peptide binds to specific G protein-coupled receptors on human cell membranes, thus providing a molecular basis for its biological effects.

Inhibiting transthyretin amyloid fibril formation via protein stabilization

Transthyretin (TTR) amyloid fibril formation is observed systemically in familial amyloid polyneuropathy and senile systemic amyloidosis and appears to be the causative agent in these diseases. Herein, we demonstrate conclusively that thyroxine (10.8 μM) inhibits TTR fibril formation efficiently in vitro and does so by stabilizing the tetramer against dissociation and the subsequent conformational changes required for amyloid fibril formation. In addition, the nonnative ligand 2,4,6-triiodophenol, which binds to TTR with slightly increased affinity also inhibits TTR fibril formation by this mechanism. Sedimentation velocity experiments were employed to show that TTR undergoes dissociation (linked to a conformational change) to form the monomeric amyloidogenic intermediate, which self-assembles into amyloid in the absence, but not in the presence of thyroxine. These results demonstrate the feasibility of using small molecules to stabilize the native fold of a potentially amyloidogenic human protein, thus preventing the conformational changes, which appear to be the common link in several human amyloid diseases. This strategy and the compounds resulting from further development should prove useful for critically evaluating the amyloid hypothesis—i.e., the putative cause-and-effect relationship between TTR amyloid deposition and the onset of familial amyloid polyneuropathy and senile systemic amyloidosis.

Statistical methods for characterizing similarities and differences between semantic structures

This paper describes a variety of statistical methods for obtaining precise quantitative estimates of the similarities and differences in the structures of semantic domains in different languages. The methods include comparing mean correlations within and between groups, principal components analysis of interspeaker correlations, and analysis of variance of speaker by question data. Methods for graphical displays of the results are also presented. The methods give convergent results that are mutually supportive and equivalent under suitable interpretation. The methods are illustrated on the semantic domain of emotion terms in a comparison of the semantic structures of native English and native Japanese speaking subjects. We suggest that, in comparative studies concerning the extent to which semantic structures are universally shared or culture-specific, both similarities and differences should be measured and compared rather than placing total emphasis on one or the other polar position.

Lagging strand replication of rolling-circle plasmids: Specific recognition of the ssoA-type origins in different gram-positive bacteria

Many bacterial plasmids replicate by a rolling-circle mechanism that involves the generation of single-stranded DNA (ssDNA) intermediates. Replication of the lagging strand of such plasmids initiates from their single strand origin (sso). Many different types of ssos have been identified. One group of ssos, termed ssoA, which have conserved sequence and structural features, function efficiently only in their natural hosts in vivo. To study the host specificity of sso sequences, we have analyzed the functions of two closely related ssoAs belonging to the staphylococcal plasmid pE194 and the streptococcal plasmid pLS1 in Staphylococcus aureus. The pLS1 ssoA functioned poorly in vivo in S. aureus as evidenced by accumulation of high levels of ssDNA but supported efficient replication in vitro in staphylococcal extracts. These results suggest that one or more host factors that are present in sufficient quantities in S. aureus cell-free extracts may be limiting in vivo. Mapping of the initiation points of lagging strand synthesis in vivo and in vitro showed that DNA synthesis initiates from specific sites within the pLS1 ssoA. These results demonstrate that specific initiation of replication can occur from the pLS1 ssoA in S. aureus although it plays a minimal role in lagging strand synthesis in vivo. Therefore, the poor functionality of the pLS1 in vivo in a nonnative host is caused by the low efficiency rather than a lack of specificity of the initiation process. We also have identified ssDNA promoters and mapped the primer RNAs synthesized by the S. aureus and Bacillus subtilis RNA polymerases from the pE194 and pLS1 ssoAs. The S. aureus RNA polymerase bound more efficiently to the native pE194 ssoA as compared with the pLS1 ssoA, suggesting that the strength of RNA polymerase–ssoA interaction may play a major role in the functionality of the ssoA sequences in Gram-positive bacteria.

Characterization of residual structure in the thermally denatured state of barnase by simulation and experiment: Description of the folding pathway

Residual structure in the denatured state of a protein may contain clues about the early events in folding. We have simulated by molecular dynamics the denatured state of barnase, which has been studied by NMR spectroscopy. An ensemble of 104 structures was generated after 2 ns of unfolding and following for a further 2 ns. The ensemble was heterogeneous, but there was nonrandom, residual structure with persistent interactions. Helical structure in the C-terminal portion of helix α1 (residues 13–17) and in helix α2 as well as a turn and nonnative hydrophobic clustering between β3 and β4 were observed, consistent with NMR data. In addition, there were tertiary contacts between residues in α1 and the C-terminal portion of the β-sheet. The simulated structures allow the rudimentary NMR data to be fleshed out. The consistency between simulation and experiment inspires confidence in the methods. A description of the folding pathway of barnase from the denatured to the native state can be constructed by combining the simulation with experimental data from φ value analysis and NMR.

Protein folding from a highly disordered denatured state: The folding pathway of chymotrypsin inhibitor 2 at atomic resolution

Previous experimental and theoretical studies have produced high-resolution descriptions of the native and folding transition states of chymotrypsin inhibitor 2 (CI2). In similar fashion, here we use a combination of NMR experiments and molecular dynamics simulations to examine the conformations populated by CI2 in the denatured state. The denatured state is highly unfolded, but there is some residual native helical structure along with hydrophobic clustering in the center of the chain. The lack of persistent nonnative structure in the denatured state reduces barriers that must be overcome, leading to fast folding through a nucleation–condensation mechanism. With the characterization of the denatured state, we have now completed our description of the folding/unfolding pathway of CI2 at atomic resolution.

The role of voice input for human-machine communication.

Optimism is growing that the near future will witness rapid growth in human-computer interaction using voice. System prototypes have recently been built that demonstrate speaker-independent real-time speech recognition, and understanding of naturally spoken utterances with vocabularies of 1000 to 2000 words, and larger. Already, computer manufacturers are building speech recognition subsystems into their new product lines. However, before this technology can be broadly useful, a substantial knowledge base is needed about human spoken language and performance during computer-based spoken interaction. This paper reviews application areas in which spoken interaction can play a significant role, assesses potential benefits of spoken interaction with machines, and compares voice with other modalities of human-computer interaction. It also discusses information that will be needed to build a firm empirical foundation for the design of future spoken and multimodal interfaces. Finally, it argues for a more systematic and scientific approach to investigating spoken input and performance with future language technology.

State of the art in continuous speech recognition.

In the past decade, tremendous advances in the state of the art of automatic speech recognition by machine have taken place. A reduction in the word error rate by more than a factor of 5 and an increase in recognition speeds by several orders of magnitude (brought about by a combination of faster recognition search algorithms and more powerful computers), have combined to make high-accuracy, speaker-independent, continuous speech recognition for large vocabularies possible in real time, on off-the-shelf workstations, without the aid of special hardware. These advances promise to make speech recognition technology readily available to the general public. This paper focuses on the speech recognition advances made through better speech modeling techniques, chiefly through more accurate mathematical modeling of speech sounds.

Training and search methods for speech recognition.

Speech recognition involves three processes: extraction of acoustic indices from the speech signal, estimation of the probability that the observed index string was caused by a hypothesized utterance segment, and determination of the recognized utterance via a search among hypothesized alternatives. This paper is not concerned with the first process. Estimation of the probability of an index string involves a model of index production by any given utterance segment (e.g., a word). Hidden Markov models (HMMs) are used for this purpose [Makhoul, J. & Schwartz, R. (1995) Proc. Natl. Acad. Sci. USA 92, 9956-9963]. Their parameters are state transition probabilities and output probability distributions associated with the transitions. The Baum algorithm that obtains the values of these parameters from speech data via their successive reestimation will be described in this paper. The recognizer wishes to find the most probable utterance that could have caused the observed acoustic index string. That probability is the product of two factors: the probability that the utterance will produce the string and the probability that the speaker will wish to produce the utterance (the language model probability). Even if the vocabulary size is moderate, it is impossible to search for the utterance exhaustively. One practical algorithm is described [Viterbi, A. J. (1967) IEEE Trans. Inf. Theory IT-13, 260-267] that, given the index string, has a high likelihood of finding the most probable utterance.

Voice-processing technologies--their application in telecommunications.

As the telecommunications industry evolves over the next decade to provide the products and services that people will desire, several key technologies will become commonplace. Two of these, automatic speech recognition and text-to-speech synthesis, will provide users with more freedom on when, where, and how they access information. While these technologies are currently in their infancy, their capabilities are rapidly increasing and their deployment in today's telephone network is expanding. The economic impact of just one application, the automation of operator services, is well over $100 million per year. Yet there still are many technical challenges that must be resolved before these technologies can be deployed ubiquitously in products and services throughout the worldwide telephone network. These challenges include: (i) High level of accuracy. The technology must be perceived by the user as highly accurate, robust, and reliable. (ii) Easy to use. Speech is only one of several possible input/output modalities for conveying information between a human and a machine, much like a computer terminal or Touch-Tone pad on a telephone. It is not the final product. Therefore, speech technologies must be hidden from the user. That is, the burden of using the technology must be on the technology itself. (iii) Quick prototyping and development of new products and services. The technology must support the creation of new products and services based on speech in an efficient and timely fashion. In this paper I present a vision of the voice-processing industry with a focus on the areas with the broadest base of user penetration: speech recognition, text-to-speech synthesis, natural language processing, and speaker recognition technologies. The current and future applications of these technologies in the telecommunications industry will be examined in terms of their strengths, limitations, and the degree to which user needs have been or have yet to be met. Although noteworthy gains have been made in areas with potentially small user bases and in the more mature speech-coding technologies, these subjects are outside the scope of this paper.

Commercial applications of speech interface technology: an industry at the threshold.

Speech interface technology, which includes automatic speech recognition, synthetic speech, and natural language processing, is beginning to have a significant impact on business and personal computer use. Today, powerful and inexpensive microprocessors and improved algorithms are driving commercial applications in computer command, consumer, data entry, speech-to-text, telephone, and voice verification. Robust speaker-independent recognition systems for command and navigation in personal computers are now available; telephone-based transaction and database inquiry systems using both speech synthesis and recognition are coming into use. Large-vocabulary speech interface systems for document creation and read-aloud proofing are expanding beyond niche markets. Today's applications represent a small preview of a rich future for speech interface technology that will eventually replace keyboards with microphones and loud-speakers to give easy accessibility to increasingly intelligent machines.

Deployment of human-machine dialogue systems.

The deployment of systems for human-to-machine communication by voice requires overcoming a variety of obstacles that affect the speech-processing technologies. Problems encountered in the field might include variation in speaking style, acoustic noise, ambiguity of language, or confusion on the part of the speaker. The diversity of these practical problems encountered in the "real world" leads to the perceived gap between laboratory and "real-world" performance. To answer the question "What applications can speech technology support today?" the concept of the "degree of difficulty" of an application is introduced. The degree of difficulty depends not only on the demands placed on the speech recognition and speech synthesis technologies but also on the expectations of the user of the system. Experience has shown that deployment of effective speech communication systems requires an iterative process. This paper discusses general deployment principles, which are illustrated by several examples of human-machine communication systems.

Toward the ultimate synthesis/recognition system.

This paper predicts speech synthesis, speech recognition, and speaker recognition technology for the year 2001, and it describes the most important research problems to be solved in order to arrive at these ultimate synthesis and recognition systems. The problems for speech synthesis include natural and intelligible voice production, prosody control based on meaning, capability of controlling synthesized voice quality and choosing individual speaking style, multilingual and multidialectal synthesis, choice of application-oriented speaking styles, capability of adding emotion, and synthesis from concepts. The problems for speech recognition include robust recognition against speech variations, adaptation/normalization to variations due to environmental conditions and speakers, automatic knowledge acquisition for acoustic and linguistic modeling, spontaneous speech recognition, naturalness and ease of human-machine interaction, and recognition of emotion. The problems for speaker recognition are similar to those for speech recognition. The research topics related to all these techniques include the use of articulatory and perceptual constraints and evaluation methods for measuring the quality of technology and systems.