extract metadata from genomic gbff files

I have >1000 .gbff.gz genomic files and I want to extract metadata from each and have metadata entries in separate columns.

In Matlab you can make use of genbankread of the Bioinformatics Toolbox. Here is an example of how to achieve what you want:

results = [];

% unzip data
gunzip('*.gbff.gz');

% process each file
files = dir('*.gbff');
for file = {files.name}
  data = genbankread(char(file));

  % process each file entry
  for i = 1:size(data, 2)
    LocusName = '';
    Definition = '';
    Organism = '';
    GenesTotal = NaN;
    GenesCoding = NaN;
    RRNAs = '';
    TRNAs = NaN;
    IsolationSource = '';
    Country = '';

    % copy fields
    if isfield(data(i), 'LocusName')
      LocusName = data(i).LocusName;
    end
    if isfield(data(i), 'Definition')
      Definition = data(i).Definition;
    end
    if isfield(data(i), 'Source')
      Organism = data(i).Source;
    end

    % parse comments
    if isfield(data(i), 'Comment')
      for j = 1:size(data(i).Comment, 1)
        tokens = regexp(data(i).Comment(j, :), ...
          '^\s*([^\s].*[^\s])\s*::\s*([^\s].*[^\s])\s*$', 'tokens');
        if ~isempty(tokens)
          switch tokens{1}{1}
            case 'Genes (total)'
              GenesTotal = str2double(tokens{1}{2});
            case 'Genes (coding)'
              GenesCoding = str2double(tokens{1}{2});
            case 'rRNAs'
              RRNAs = tokens{1}{2};
            case 'tRNAs'
              TRNAs = str2double(tokens{1}{2});
          end
        end
      end
    end

    % parse features
    if isfield(data(i), 'Features')
      Feature = '';
      for j = 1:size(data(i).Features, 1)
        tokens = regexp(data(i).Features(j, :), '^(\w+)', 'tokens');
        if isempty(tokens)
          tokens = regexp(data(i).Features(j, :), ...
            '^\s+/(\w+)="([^"]+)"', 'tokens');
          if ~isempty(tokens)
            switch Feature
              case 'source'
                switch tokens{1}{1}
                  case 'isolation_source'
                    IsolationSource = tokens{1}{2};
                  case 'country'
                    Country = tokens{1}{2};
                end
            end
          end
        else
          Feature = tokens{1}{1};
        end
      end
    end

    % append entries to results
    results = [results; struct( ...
      'File', char(file), 'LocusName', LocusName, 'Definition', Definition, ...
      'Organism', Organism, 'GenesTotal', GenesTotal, ...
      'GenesCoding', GenesCoding, 'RRNAs', RRNAs, 'TRNAs', TRNAs, ...
      'IsolationSource', IsolationSource, 'Country', Country)];
  end
end

% data is in variable results